q2-feature-table

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

Combines feature data objects which may or may not contain data for the same features. If different feature data is present for the same feature id in the inputs, the data from the first will be propagated to the result.

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Combines a pair of feature data objects which may or may not contain data for the same features. If different feature data is present for the same feature id in the inputs, the data from the first will be propagated to the result.

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Filter samples from table based on frequency and/or metadata. Any features with a frequency of zero after sample filtering will also be removed. See the filtering tutorial on https://docs.qiime2.org for additional details.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Filter features based on the relative abundance in a certain portion of samples (i.e., features must have a relative abundance of at least abundance in at least prevalence number of samples). Any samples with a frequency of zero after feature filtering will also be removed.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Filter features from table based on frequency and/or metadata. Any samples with a frequency of zero after feature filtering will also be removed. See the filtering tutorial on https://docs.qiime2.org for additional details.

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Filter features from sequences based on a feature table or metadata. See the filtering tutorial on https://docs.qiime2.org for additional details. This method can filter based on ids in a table or a metadata file, but not both (i.e., the table and metadata options are mutually exclusive).

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Identify "core" features, which are features observed in a user-defined fraction of the samples. Since the core features are a function of the fraction of samples that the feature must be observed in to be considered core, this is computed over a range of fractions defined by the min_fraction, max_fraction, and steps parameters.

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Generate a heatmap representation of a feature table with optional clustering on both the sample and feature axes. Tip: To generate a heatmap containing taxonomic annotations, use qiime taxa collapse to collapse the feature table at the desired taxonomic level.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to visualize.[required]

Parameters¶

sample_metadata: MetadataColumn[Categorical]: Annotate the sample IDs with these sample metadata values. When metadata is present and cluster='feature', samples will be sorted by the metadata values.[optional]
feature_metadata: MetadataColumn[Categorical]: Annotate the feature IDs with these feature metadata values. When metadata is present and cluster='sample', features will be sorted by the metadata values.[optional]
normalize: Bool: Normalize the feature table by adding a psuedocount of 1 and then taking the log10 of the table.[default: True]
title: Str: Optional custom plot title.[optional]
metric: Str % Choices('braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice', 'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis', 'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean', 'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'): Metrics exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'euclidean']
method: Str % Choices('average', 'centroid', 'complete', 'median', 'single', 'ward', 'weighted'): Clustering methods exposed by seaborn (see http://seaborn.pydata.org/generated/seaborn.clustermap.html#seaborn.clustermap for more detail).[default: 'average']
cluster: Str % Choices('both', 'features', 'none', 'samples'): Specify which axes to cluster.[default: 'both']
color_scheme: Str % Choices('Accent', 'Accent_r', 'Blues', 'Blues_r', 'BrBG', 'BrBG_r', 'BuGn', 'BuGn_r', 'BuPu', 'BuPu_r', 'CMRmap', 'CMRmap_r', 'Dark2', 'Dark2_r', 'GnBu', 'GnBu_r', 'Greens', 'Greens_r', 'Greys', 'Greys_r', 'OrRd', 'OrRd_r', 'Oranges', 'Oranges_r', 'PRGn', 'PRGn_r', 'Paired', 'Paired_r', 'Pastel1', 'Pastel1_r', 'Pastel2', 'Pastel2_r', 'PiYG', 'PiYG_r', 'PuBu', 'PuBuGn', 'PuBuGn_r', 'PuBu_r', 'PuOr', 'PuOr_r', 'PuRd', 'PuRd_r', 'Purples', 'Purples_r', 'RdBu', 'RdBu_r', 'RdGy', 'RdGy_r', 'RdPu', 'RdPu_r', 'RdYlBu', 'RdYlBu_r', 'RdYlGn', 'RdYlGn_r', 'Reds', 'Reds_r', 'Set1', 'Set1_r', 'Set2', 'Set2_r', 'Set3', 'Set3_r', 'Spectral', 'Spectral_r', 'Vega10', 'Vega10_r', 'Vega20', 'Vega20_r', 'Vega20b', 'Vega20b_r', 'Vega20c', 'Vega20c_r', 'Wistia', 'Wistia_r', 'YlGn', 'YlGnBu', 'YlGnBu_r', 'YlGn_r', 'YlOrBr', 'YlOrBr_r', 'YlOrRd', 'YlOrRd_r', 'afmhot', 'afmhot_r', 'autumn', 'autumn_r', 'binary', 'binary_r', 'bone', 'bone_r', 'brg', 'brg_r', 'bwr', 'bwr_r', 'cividis', 'cividis_r', 'cool', 'cool_r', 'coolwarm', 'coolwarm_r', 'copper', 'copper_r', 'cubehelix', 'cubehelix_r', 'flag', 'flag_r', 'gist_earth', 'gist_earth_r', 'gist_gray', 'gist_gray_r', 'gist_heat', 'gist_heat_r', 'gist_ncar', 'gist_ncar_r', 'gist_rainbow', 'gist_rainbow_r', 'gist_stern', 'gist_stern_r', 'gist_yarg', 'gist_yarg_r', 'gnuplot', 'gnuplot2', 'gnuplot2_r', 'gnuplot_r', 'gray', 'gray_r', 'hot', 'hot_r', 'hsv', 'hsv_r', 'icefire', 'icefire_r', 'inferno', 'inferno_r', 'jet', 'jet_r', 'magma', 'magma_r', 'mako', 'mako_r', 'nipy_spectral', 'nipy_spectral_r', 'ocean', 'ocean_r', 'pink', 'pink_r', 'plasma', 'plasma_r', 'prism', 'prism_r', 'rainbow', 'rainbow_r', 'rocket', 'rocket_r', 'seismic', 'seismic_r', 'spectral', 'spectral_r', 'spring', 'spring_r', 'summer', 'summer_r', 'tab10', 'tab10_r', 'tab20', 'tab20_r', 'tab20b', 'tab20b_r', 'tab20c', 'tab20c_r', 'terrain', 'terrain_r', 'viridis', 'viridis_r', 'vlag', 'vlag_r', 'winter', 'winter_r'): The matplotlib colorscheme to generate the heatmap with.[default: 'rocket']

Outputs¶

visualization: Visualization: <no description>[required]

feature-table summarize-plus¶

Generate visual and tabular summaries of a feature table. Tabulate sample and feature frequencies.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

metadata: Metadata: The sample metadata.[optional]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]
sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]
summary: Visualization: Visual summary of feature table[required]

Examples¶

feature_table_summarize_plus¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'

qiime feature-table summarize-plus \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza \
  --o-sample-frequencies sample-frequencies.qza \
  --o-summary visual summary.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, sample_frequencies, visual_summary_viz = feature_table_actions.summarize_plus(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize-plus tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for each new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize-plus [...] : feature_frequencies.qza`	`feature-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : sample_frequencies.qza`	`sample-frequencies.qza`
`#: qiime2 feature-table summarize-plus [...] : summary.qzv`	`visual summary.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize-plus/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize_plus(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies
sample_frequencies <- action_results$sample_frequencies
visual_summary_viz <- action_results$summary

feature-table.qza | download | view
feature-frequencies.qza | download | view
sample-frequencies.qza | download | view
visual summary.qzv | download | view

This is a QIIME 2 plugin supporting operations on sample by feature tables, such as filtering, merging, and transforming tables.

version: 2024.10.0
website: https://github.com/qiime2/q2-feature-table
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
rarefy	method	Rarefy table
subsample-ids	method	Subsample table
presence-absence	method	Convert to presence/absence
relative-frequency	method	Convert to relative frequencies
transpose	method	Transpose a feature table.
group	method	Group samples or features by a metadata column
merge	method	Combine multiple tables
merge-seqs	method	Combine collections of feature sequences
merge-taxa	method	Combine collections of feature taxonomies
rename-ids	method	Renames sample or feature ids in a table
filter-samples	method	Filter samples from table
filter-features-conditionally	method	Filter features from a table based on abundance and prevalence
filter-features	method	Filter features from table
filter-seqs	method	Filter features from sequences
split	method	Split one feature table into many
tabulate-feature-frequencies	method	Tabulate feature frequencies
tabulate-sample-frequencies	method	Tabulate sample frequencies
summarize	visualizer	Summarize table
tabulate-seqs	visualizer	View sequence associated with each feature
core-features	visualizer	Identify core features in table
heatmap	visualizer	Generate a heatmap representation of a feature table
summarize-plus	pipeline	Summarize table plus

feature-table rarefy¶

Subsample frequencies from all samples so that the sum of frequencies in each sample is equal to sampling-depth.

Citations¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to be rarefied.[required]

Parameters¶

sampling_depth: Int % Range(1, None): The total frequency that each sample should be rarefied to. Samples where the sum of frequencies is less than the sampling depth will be not be included in the resulting table.[required]
with_replacement: Bool: Rarefy with replacement by sampling from the multinomial distribution instead of rarefying without replacement.[default: False]

Outputs¶

rarefied_table: FeatureTable[Frequency]: The resulting rarefied feature table.[required]

feature-table subsample-ids¶

Randomly pick samples or features, without replacement, from the table.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be sampled.[required]

Parameters¶

subsampling_depth: Int % Range(1, None): The total number of samples or features to be randomly sampled. Samples or features that are reduced to a zero sum will not be included in the resulting table.[required]
axis: Str % Choices('sample', 'feature'): The axis to sample over. If "sample" then samples will be randomly selected to be retained. If "feature" then a random set of features will be selected to be retained.[required]

Outputs¶

sampled_table: FeatureTable[Frequency]: The resulting subsampled feature table.[required]

feature-table presence-absence¶

Convert frequencies to binary values indicating presence or absence of a feature in a sample.

Inputs¶

table: FeatureTable[Frequency | RelativeFrequency]: The feature table to be converted into presence/absence abundances.[required]

Outputs¶

presence_absence_table: FeatureTable[PresenceAbsence]: The resulting presence/absence feature table.[required]

feature-table relative-frequency¶

Convert frequencies to relative frequencies by dividing each frequency in a sample by the sum of frequencies in that sample.

Inputs¶

table: FeatureTable[Frequency]: The feature table to be converted into relative frequencies.[required]

Outputs¶

relative_frequency_table: FeatureTable[RelativeFrequency]: The resulting relative frequency feature table.[required]

feature-table transpose¶

Transpose the rows and columns (typically samples and features) of a feature table.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table to be transposed.[required]

Outputs¶

transposed_feature_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting transposed feature table.[required]

feature-table group¶

Group samples or features in a feature table using metadata to define the mapping of IDs to a group.

Inputs¶

table: FeatureTable[Frequency]: The table to group samples or features on.[required]

Parameters¶

axis: Str % Choices('feature', 'sample'): Along which axis to group. Each ID in the given axis must exist in metadata.[required]
metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will become a new ID for the table on the given axis.[required]
mode: Str % Choices('mean-ceiling', 'median-ceiling', 'sum'): How to combine samples or features within a group. sum will sum the frequencies across all samples or features within a group; mean-ceiling will take the ceiling of the mean of these frequencies; median-ceiling will take the ceiling of the median of these frequencies.[required]

Outputs¶

grouped_table: FeatureTable[Frequency]: A table that has been grouped along the given axis. IDs on that axis are replaced by values in the metadata column.[required]

Examples¶

group_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'

# Combine samples from the same body-site into single sample. Feature
# frequencies will be the median across the samples being combined, rounded
# up to the nearest whole number.
qiime feature-table group \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --m-metadata-column body-site \
  --p-mode median-ceiling \
  --p-axis sample \
  --o-grouped-table body-site-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

body_site_mdc = sample_metadata_md.get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
body_site_table, = feature_table_actions.group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: sample-metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.

Using the qiime2 feature-table group tool:

Set "table" to #: feature-table.qza
Set "axis" to sample
For "metadata":
1. Leave as Metadata from TSV
2. Set "Metadata Source" to sample-metadata.tsv
3. Set "Column Name" to body-site
Set "mode" to median-ceiling
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table group [...] : grouped_table.qza`	`body-site-table.qza`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/group/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

body_site_mdc <- sample_metadata_md$get_column('body-site')
# Combine samples from the same body-site into single sample. Feature frequencies will be the median across the samples being combined, rounded up to the nearest whole number.
action_results <- feature_table_actions$group(
    table=feature_table,
    metadata=body_site_mdc,
    mode='median-ceiling',
    axis='sample',
)
body_site_table <- action_results$grouped_table

feature-table.qza | download | view
sample-metadata.tsv | download
body-site-table.qza | download | view

feature-table merge¶

Combines feature tables using the overlap_method provided.

Inputs¶

tables: List[FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]]: The collection of feature tables to be merged.[required]

Parameters¶

overlap_method: Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample', 'sum') | Str % Choices('average', 'error_on_overlapping_feature', 'error_on_overlapping_sample') | Str % Choices('error_on_overlapping_feature', 'error_on_overlapping_sample', 'union'): Method for handling overlapping ids.[default: 'error_on_overlapping_sample']

Outputs¶

merged_table: FeatureTable[Frequency] | FeatureTable[RelativeFrequency] | FeatureTable[PresenceAbsence]: The resulting merged feature table.[required]

Examples¶

feature_table_merge_two_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/1/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2),
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
merged-table.qza | download | view

feature_table_merge_three_tables¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'

wget -O 'feature-table2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'

wget -O 'feature-table3.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'

qiime feature-table merge \
  --i-tables feature-table1.qza feature-table2.qza feature-table3.qza \
  --p-overlap-method sum \
  --o-merged-table merged-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn = 'feature-table1.qza'
request.urlretrieve(url, fn)
feature_table1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn = 'feature-table2.qza'
request.urlretrieve(url, fn)
feature_table2 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn = 'feature-table3.qza'
request.urlretrieve(url, fn)
feature_table3 = Artifact.load(fn)

merged_table, = feature_table_actions.merge(
    tables=[feature_table1, feature_table2, feature_table3],
    overlap_method='sum',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table1.qza'
fn <- 'feature-table1.qza'
request$urlretrieve(url, fn)
feature_table1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table2.qza'
fn <- 'feature-table2.qza'
request$urlretrieve(url, fn)
feature_table2 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge/2/feature-table3.qza'
fn <- 'feature-table3.qza'
request$urlretrieve(url, fn)
feature_table3 <- Artifact$load(fn)

action_results <- feature_table_actions$merge(
    tables=list(feature_table1, feature_table2, feature_table3),
    overlap_method='sum',
)
merged_table <- action_results$merged_table

feature-table1.qza | download | view
feature-table2.qza | download | view
feature-table3.qza | download | view
merged-table.qza | download | view

feature-table merge-seqs¶

Inputs¶

data: List[FeatureData[Sequence]]: The collection of feature sequences to be merged.[required]

Outputs¶

merged_data: FeatureData[Sequence]: The resulting collection of feature sequences containing all feature sequences provided.[required]

Examples¶

feature_table_merge_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'seqs1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'

wget -O 'seqs2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'

qiime feature-table merge-seqs \
  --i-data seqs1.qza seqs2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn = 'seqs1.qza'
request.urlretrieve(url, fn)
seqs1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn = 'seqs2.qza'
request.urlretrieve(url, fn)
seqs2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_seqs(
    data=[seqs1, seqs2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs1.qza'
fn <- 'seqs1.qza'
request$urlretrieve(url, fn)
seqs1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-seqs/1/seqs2.qza'
fn <- 'seqs2.qza'
request$urlretrieve(url, fn)
seqs2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_seqs(
    data=list(seqs1, seqs2),
)
merged_data <- action_results$merged_data

seqs1.qza | download | view
seqs2.qza | download | view
merged-data.qza | download | view

feature-table merge-taxa¶

Inputs¶

data: List[FeatureData[Taxonomy]]: The collection of feature taxonomies to be merged.[required]

Outputs¶

merged_data: FeatureData[Taxonomy]: The resulting collection of feature taxonomies containing all feature taxonomies provided.[required]

Examples¶

feature_table_merge_taxa¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'tax1.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'

wget -O 'tax2.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'

qiime feature-table merge-taxa \
  --i-data tax1.qza tax2.qza \
  --o-merged-data merged-data.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn = 'tax1.qza'
request.urlretrieve(url, fn)
tax1 = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn = 'tax2.qza'
request.urlretrieve(url, fn)
tax2 = Artifact.load(fn)

merged_data, = feature_table_actions.merge_taxa(
    data=[tax1, tax2],
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax1.qza'
fn <- 'tax1.qza'
request$urlretrieve(url, fn)
tax1 <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/merge-taxa/1/tax2.qza'
fn <- 'tax2.qza'
request$urlretrieve(url, fn)
tax2 <- Artifact$load(fn)

action_results <- feature_table_actions$merge_taxa(
    data=list(tax1, tax2),
)
merged_data <- action_results$merged_data

tax1.qza | download | view
tax2.qza | download | view
merged-data.qza | download | view

feature-table rename-ids¶

Renames the sample or feature ids in a feature table using metadata to define the new ids.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to be renamed[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A metadata column defining the new ids. Each original id must map to a new unique id. If strict mode is used, then every id in the original table must have a new id.[required]
axis: Str % Choices('feature', 'sample'): Along which axis to rename the ids.[default: 'sample']
strict: Bool: Whether the naming needs to be strict (each id in the table must have a new id). Otherwise, only the ids described in metadata will be renamed and the others will keep their original id names.[default: False]

Outputs¶

renamed_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: A table which has new ids, where the ids are replaced by values in the metadata column.[required]

feature-table filter-samples¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which samples should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a sample must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_features: Int: The minimum number of features that a sample must have to be retained.[default: 0]
max_features: Int: The maximum number of features that a sample can have to be retained. If no value is provided this will default to infinity (i.e., no maximum feature filter will be applied).[optional]
metadata: Metadata: Sample metadata used with where parameter when selecting samples to retain, or with exclude_ids when selecting samples to discard.[optional]
where: Str: SQLite WHERE clause specifying sample metadata criteria that must be met to be included in the filtered feature table. If not provided, all samples in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the samples selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_features: Bool: If true, features which are not present in any retained samples are dropped.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by sample.[required]

Examples¶

filter_to_subject1¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/1/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_skin¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site] IN ("left palm", "right palm")' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/2/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site] IN ("left palm", "right palm")',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/3/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_gut_or_abx¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[body-site]="gut" OR [reported-antibiotic-usage]="Yes"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/4/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[body-site]="gut" OR [reported-antibiotic-usage]="Yes"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_to_subject1_not_gut¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'

wget -O 'sample-metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --m-metadata-file sample-metadata.tsv \
  --p-where '[subject]="subject-1" AND NOT [body-site]="gut"' \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn = 'sample-metadata.tsv'
request.urlretrieve(url, fn)
sample_metadata_md = Metadata.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/5/sample-metadata.tsv'
fn <- 'sample-metadata.tsv'
request$urlretrieve(url, fn)
sample_metadata_md <- Metadata$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    metadata=sample_metadata_md,
    where='[subject]="subject-1" AND NOT [body-site]="gut"',
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
sample-metadata.tsv | download
filtered-table.qza | download | view

filter_min_features¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-features 10 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_features=10,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/6/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_features=10L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

filter_min_frequency¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'

qiime feature-table filter-samples \
  --i-table feature-table.qza \
  --p-min-frequency 1500 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_samples(
    table=feature_table,
    min_frequency=1500,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-samples/7/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_samples(
    table=feature_table,
    min_frequency=1500L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features-conditionally¶

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The feature table from which features should be filtered.[required]

Parameters¶

abundance: Float % Range(0, 1): The minimum relative abundance for a feature to be retained.[required]
prevalence: Float % Range(0, 1): The minimum portion of samples that a feature must have a relative abundance of at least abundance to be retained.[required]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The resulting feature table filtered by feature.[required]

Examples¶

feature_table_filter_features_conditionally¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'

# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
  --i-table feature-table.qza \
  --p-abundance 0.01 \
  --p-prevalence 0.34 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
filtered_table, = feature_table_actions.filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features-conditionally/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

# Retain only features with at least 1%% abundance in at least 34%% of samples.
action_results <- feature_table_actions$filter_features_conditionally(
    table=feature_table,
    abundance=0.01,
    prevalence=0.34,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table from which features should be filtered.[required]

Parameters¶

min_frequency: Int: The minimum total frequency that a feature must have to be retained.[default: 0]
max_frequency: Int: The maximum total frequency that a feature can have to be retained. If no value is provided this will default to infinity (i.e., no maximum frequency filter will be applied).[optional]
min_samples: Int: The minimum number of samples that a feature must be observed in to be retained.[default: 0]
max_samples: Int: The maximum number of samples that a feature can be observed in to be retained. If no value is provided this will default to infinity (i.e., no maximum sample filter will be applied).[optional]
metadata: Metadata: Feature metadata used with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the feature table will be retained.[optional]
exclude_ids: Bool: If true, the features selected by metadata or where parameters will be excluded from the filtered table instead of being retained.[default: False]
filter_empty_samples: Bool: If true, drop any samples where none of the retained features are present.[default: True]
allow_empty_table: Bool: If true, the filtered table may be empty. Default behavior is to raise an error if the filtered table is empty.[default: False]

Outputs¶

filtered_table: FeatureTable[Frequency]: The resulting feature table filtered by feature.[required]

Examples¶

filter_features_min_samples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'

qiime feature-table filter-features \
  --i-table feature-table.qza \
  --p-min-samples 2 \
  --o-filtered-table filtered-table.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

filtered_table, = feature_table_actions.filter_features(
    table=feature_table,
    min_samples=2,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/filter-features/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$filter_features(
    table=feature_table,
    min_samples=2L,
)
filtered_table <- action_results$filtered_table

feature-table.qza | download | view
filtered-table.qza | download | view

feature-table filter-seqs¶

Inputs¶

data: FeatureData[Sequence¹ | AlignedSequence²]: The sequences from which features should be filtered.[required]
table: FeatureTable[Frequency]: Table containing feature ids used for id-based filtering.[optional]

Parameters¶

metadata: Metadata: Feature metadata used for id-based filtering, with where parameter when selecting features to retain, or with exclude_ids when selecting features to discard.[optional]
where: Str: SQLite WHERE clause specifying feature metadata criteria that must be met to be included in the filtered feature table. If not provided, all features in metadata that are also in the sequences will be retained.[optional]
exclude_ids: Bool: If true, the features selected by the metadata (with or without the where parameter) or table parameter will be excluded from the filtered sequences instead of being retained.[default: False]

Outputs¶

filtered_data: FeatureData[Sequence¹ | AlignedSequence²]: The resulting filtered sequences.[required]

feature-table split¶

Splits one feature table into many feature tables, where splits are defined by values in metadata column.

Inputs¶

table: FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]: The table to split.[required]

Parameters¶

metadata: MetadataColumn[Categorical]: A column defining the groups. Each unique value will define a split feature table.[required]
filter_empty_features: Bool: If true, features which are not present in a split feature table are dropped.[default: True]

Outputs¶

tables: Collection[FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]]: Directory where feature tables split based on metadata values should be written.[required]

feature-table tabulate-feature-frequencies¶

Tabulate sample count and total frequency per feature.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

feature_frequencies: ImmutableMetadata: Per-sample and total frequencies per feature.[required]

Examples¶

feature_table_tabulate_feature_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'

qiime feature-table tabulate-feature-frequencies \
  --i-table feature-table.qza \
  --o-feature-frequencies feature-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

feature_frequencies, = feature_table_actions.tabulate_feature_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-feature-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_feature_frequencies(
    table=feature_table,
)
feature_frequencies <- action_results$feature_frequencies

feature-table.qza | download | view
feature-frequencies.qza | download | view

feature-table tabulate-sample-frequencies¶

Tabulate feature count and total frequency per sample.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence | RelativeFrequency]: The input feature table.[required]

Outputs¶

sample_frequencies: ImmutableMetadata: Observed feature count and total frequencies per sample.[required]

Examples¶

feature_table_tabulate_sample_frequencies¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'

qiime feature-table tabulate-sample-frequencies \
  --i-table feature-table.qza \
  --o-sample-frequencies sample-frequencies.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

sample_frequencies, = feature_table_actions.tabulate_sample_frequencies(
    table=feature_table,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-sample-frequencies/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_sample_frequencies(
    table=feature_table,
)
sample_frequencies <- action_results$sample_frequencies

feature-table.qza | download | view
sample-frequencies.qza | download | view

feature-table summarize¶

Generate visual and tabular summaries of a feature table.

Inputs¶

table: FeatureTable[Frequency | PresenceAbsence]: The feature table to be summarized.[required]

Parameters¶

sample_metadata: Metadata: The sample metadata.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_summarize¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'feature-table.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'

qiime feature-table summarize \
  --i-table feature-table.qza \
  --o-visualization table.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn = 'feature-table.qza'
request.urlretrieve(url, fn)
feature_table = Artifact.load(fn)

table_viz, = feature_table_actions.summarize(
    table=feature_table,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: feature-table.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table summarize tool:

Set "table" to #: feature-table.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table summarize [...] : visualization.qzv`	`table.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/summarize/1/feature-table.qza'
fn <- 'feature-table.qza'
request$urlretrieve(url, fn)
feature_table <- Artifact$load(fn)

action_results <- feature_table_actions$summarize(
    table=feature_table,
)
table_viz <- action_results$visualization

feature-table.qza | download | view
table.qzv | download | view

feature-table tabulate-seqs¶

Generate tabular view of feature identifier to sequence mapping, including links to BLAST each sequence against the NCBI nt database.

Citations¶

Inputs¶

data: FeatureData[Sequence | AlignedSequence]: The feature sequences to be tabulated.[required]
taxonomy: Collection[FeatureData[Taxonomy]]: The taxonomic classifications of the tabulated features.[optional]

Parameters¶

metadata: Metadata: Any additional metadata for the tabulated features.[optional]
merge_method: Str % Choices('strict', 'union', 'intersect'): Method that joins data sets[default: 'strict']

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

feature_table_tabulate_seqs¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn = 'rep-seqs.qza'
request.urlretrieve(url, fn)
rep_seqs = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs.qza
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/1/rep-seqs.qza'
fn <- 'rep-seqs.qza'
request$urlretrieve(url, fn)
rep_seqs <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs,
)
rep_seqs_viz <- action_results$visualization

rep-seqs.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_single_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-single-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'

wget -O 'single-taxonomy.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-single-taxon.qza \
  --i-taxonomy single-taxonomy.qza \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn = 'rep-seqs-single-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_single_taxon = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn = 'single-taxonomy.qza'
request.urlretrieve(url, fn)
single_taxonomy = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=[single_taxonomy],
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-single-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: single-taxonomy.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-single-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: ['single-taxonomy.qza']
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/rep-seqs-single-taxon.qza'
fn <- 'rep-seqs-single-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_single_taxon <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/2/single-taxonomy.qza'
fn <- 'single-taxonomy.qza'
request$urlretrieve(url, fn)
single_taxonomy <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_single_taxon,
    taxonomy=list(single_taxonomy),
)
rep_seqs_viz <- action_results$visualization

rep-seqs-single-taxon.qza | download | view
single-taxonomy.qza | download | view
rep-seqs.qzv | download | view

feature_table_tabulate_seqs_multi_taxon¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'rep-seqs-multi-taxon.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'

qiime feature-table tabulate-seqs \
  --i-data rep-seqs-multi-taxon.qza \
  --i-taxonomy multi-taxonomy/ \
  --o-visualization rep-seqs.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.feature_table.actions as feature_table_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn = 'rep-seqs-multi-taxon.qza'
request.urlretrieve(url, fn)
rep_seqs_multi_taxon = Artifact.load(fn)

rep_seqs_viz, = feature_table_actions.tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)

Using the Upload Data tool:

On the first tab (Regular), press the Paste/Fetch data button at the bottom.
1. Set "Name" (first text-field) to: rep-seqs-multi-taxon.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 feature-table tabulate-seqs tool:

Set "data" to #: rep-seqs-multi-taxon.qza
Expand the additional options section
- Set "taxonomy" to #: multi-taxonomy/
Press the Execute button.

Once completed, for the new entry in your history, use the Edit button to set the name as follows:

(Renaming is optional, but it will make any subsequent steps easier to complete.)

History Name	"Name" to set (be sure to press [Save])
`#: qiime2 feature-table tabulate-seqs [...] : visualization.qzv`	`rep-seqs.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
feature_table_actions <- import("qiime2.plugins.feature_table.actions")
request <- import("urllib")$request

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/feature-table/tabulate-seqs/3/rep-seqs-multi-taxon.qza'
fn <- 'rep-seqs-multi-taxon.qza'
request$urlretrieve(url, fn)
rep_seqs_multi_taxon <- Artifact$load(fn)

action_results <- feature_table_actions$tabulate_seqs(
    data=rep_seqs_multi_taxon,
    taxonomy=multi_taxonomy_artifact_collection,
)
rep_seqs_viz <- action_results$visualization

rep-seqs-multi-taxon.qza | download | view
rep-seqs.qzv | download | view

feature-table core-features¶

Inputs¶

table: FeatureTable[Frequency]: The feature table to use in core features calculations.[required]

Parameters¶

min_fraction: Float % Range(0.0, 1.0, inclusive_start=False): The minimum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 0.5]
max_fraction: Float % Range(0.0, 1.0, inclusive_end=True): The maximum fraction of samples that a feature must be observed in for that feature to be considered a core feature.[default: 1.0]
steps: Int % Range(2, None): The number of steps to take between min_fraction and max_fraction for core features calculations. This parameter has no effect if min_fraction and max_fraction are the same value.[default: 11]

Outputs¶

visualization: Visualization: <no description>[required]

feature-table heatmap¶

Citations¶