q2-stats

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched]: <no description>[required]

Parameters¶

ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: True]

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'

qiime stats wilcoxon-srt-facet \
  --i-distribution dist.qza \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt_facet(
    distribution=dist,
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt_facet(
    distribution=dist,
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

stats alpha-group-significance¶

Will select between Wilcoxon SRT and Mann-Whitney U depending on the presence of repeated measures.

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the results to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the results to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: Dist1D generated by metadata and alpha diversity.[required]
stats: StatsTable[Pairwise]: A stats table of the per-group/timepoint results[required]
raincloud: Visualization: A visualization of the distribution and statistics[required]

Examples¶

alpha_group_significance_faith_pd¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'alpha-div-faith-pd.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'

wget -O 'metadata.tsv' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'

qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --p-subject mouse_id \
  --p-timepoint days_post_transplant \
  --o-distribution dist.qza \
  --o-stats stats.qza \
  --o-raincloud raincloud.qzv
qiime stats alpha-group-significance \
  --i-alpha-diversity alpha-div-faith-pd.qza \
  --m-metadata-file metadata.tsv \
  --p-columns genotype donor_status \
  --o-distribution dist2.qza \
  --o-stats stats2.qza \
  --o-raincloud raincloud2.qzv

from qiime2 import Artifact
from qiime2 import Metadata
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn = 'alpha-div-faith-pd.qza'
request.urlretrieve(url, fn)
alpha_div_faith_pd = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn = 'metadata.tsv'
request.urlretrieve(url, fn)
metadata_md = Metadata.load(fn)

dist, stats, raincloud_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist2, stats2, raincloud2_viz = stats_actions.alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=['genotype', 'donor_status'],
)

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: alpha-div-faith-pd.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.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: metadata.tsv
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
Expand the additional options section
1. Set "subject" to mouse_id
2. Set "timepoint" to days_post_transplant
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 stats alpha-group-significance [...] : distribution.qza`	`dist.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud.qzv`

Using the qiime2 stats alpha-group-significance tool:

Set "alpha_diversity" to #: alpha-div-faith-pd.qza
For "metadata":
- Perform the following steps.
  1. Leave as Metadata from TSV
  2. Set "Metadata Source" to metadata.tsv
For "columns", use the + columns button to add the corresponding values:
1. Add "element" set to genotype
2. Add "element" set to donor_status
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 stats alpha-group-significance [...] : distribution.qza`	`dist2.qza`
`#: qiime2 stats alpha-group-significance [...] : stats.qza`	`stats2.qza`
`#: qiime2 stats alpha-group-significance [...] : raincloud.qzv`	`raincloud2.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
Metadata <- import("qiime2")$Metadata
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/alpha-div-faith-pd.qza'
fn <- 'alpha-div-faith-pd.qza'
request$urlretrieve(url, fn)
alpha_div_faith_pd <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/alpha-group-significance/1/metadata.tsv'
fn <- 'metadata.tsv'
request$urlretrieve(url, fn)
metadata_md <- Metadata$load(fn)

action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
    subject='mouse_id',
    timepoint='days_post_transplant',
)
dist <- action_results$distribution
stats <- action_results$stats
raincloud_viz <- action_results$raincloud
action_results <- stats_actions$alpha_group_significance(
    alpha_diversity=alpha_div_faith_pd,
    metadata=metadata_md,
    columns=list('genotype', 'donor_status'),
)
dist2 <- action_results$distribution
stats2 <- action_results$stats
raincloud2_viz <- action_results$raincloud

alpha-div-faith-pd.qza | download | view
metadata.tsv | download
dist.qza | download | view
stats.qza | download | view
raincloud.qzv | download | view
dist2.qza | download | view
stats2.qza | download | view
raincloud2.qzv | download | view

This QIIME 2 plugin supports statistical analyses.

version: 0+untagged.28.g5ad6f19
website: https://github.com/qiime2/q2-stats
user support:: Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

Name	Type	Short Description
mann-whitney-u	method	Mann-Whitney U Test
wilcoxon-srt	method	Wilcoxon Signed Rank Test
facet-within	method	Facet within outer group
facet-across	method	Facet across outer group
collate-stats	method	Combine and FDR correct multiple stats
~~prep-alpha-distribution~~	method	Alpha diversity to Dist1D
plot-rainclouds	visualizer	Raincloud plots
mann-whitney-u-facet	pipeline	Per-facet Mann-Whitney U Test
wilcoxon-srt-facet	pipeline	Per-facet Wilcoxon Signed Rank Test
~~alpha-group-significance~~	pipeline	Alpha group significance test and plot

Artifact Classes¶

Formats¶

stats mann-whitney-u¶

Citations¶

Inputs¶

distribution: Dist1D[Unordered | Ordered, Independent]: <no description>[required]
against_each: Dist1D[Unordered | Ordered, Matched | Independent]: <no description>[optional]

Parameters¶

compare: Str % Choices('reference', 'all-pairwise'): The comparison that will be used to analyze the input distribution. Either "reference" or "all-pairwise" must be selected. The "reference" comparison defines Group A as the reference/control provided to reference_group (sourced from either reference_column or control_column), and Group B as all other groups. The "all-pairwise" comparison compares all groups to all other groups. If against_each is used, this will define Group B.[required]
reference_group: Str: If "reference" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions, "asymptotic" will use a normal distribution, and "auto" will use either "exact" when one of the groups has less than 8 observations and there are no ties, otherwise "asymptotic".[default: 'auto']

Outputs¶

stats: StatsTable[Pairwise]: The Mann-Whitney U table for either the "reference" or "all-pairwise" comparison.[required]

Examples¶

mann_whitney_pairwise¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'

wget -O 'refdist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'

qiime stats mann-whitney-u \
  --i-distribution refdist.qza \
  --p-compare all-pairwise \
  --i-against-each timedist.qza \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn = 'refdist.qza'
request.urlretrieve(url, fn)
refdist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u/1/refdist.qza'
fn <- 'refdist.qza'
request$urlretrieve(url, fn)
refdist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u(
    distribution=refdist,
    compare='all-pairwise',
    against_each=timedist,
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
refdist.qza | download | view
stats.qza | download | view

stats wilcoxon-srt¶

Citations¶

Inputs¶

distribution: Dist1D[Ordered, Matched]: <no description>[required]

Parameters¶

compare: Str % Choices('baseline', 'consecutive'): The type of comparison that will be used to analyze the input distribution. The "baseline" comparison defines Group A as the timepoint provided to baseline_group (sourced from time_column), and Group B as all other timepoints contained in time_column. The "consecutive" comparison defines Group A as "timepoint n", and Group B as "timepoint n+1" (both sourced from time_column).[required]
baseline_group: Str: If "baseline" is the selected comparison, this is the column that will be used to compare all other groups against.[optional]
alternative: Str % Choices('two-sided', 'greater', 'less'): The "two-sided" alternative hypothesis is that the median of Group A does not equal the median of Group B. The "greater" alternative hypothesis is that the median of group A is greater than the median of Group B. The "less" alternative hypothesis is that the median of group A is less than the median of Group B.[default: 'two-sided']
p_val_approx: Str % Choices('auto', 'exact', 'asymptotic'): "exact" will calculate an exact p-value for distributions of up to 25 (inclusive) measurements, "asymptotic" will use a normal distribution, and "auto" will use either "exact" or "approx" depending on size.[default: 'auto']
ignore_empty_comparator: Bool: Ignore any group that does not have any overlapping subjects with comparison group. These groups will have NaNs in the stats table output[default: False]

Outputs¶

stats: StatsTable[Pairwise]: The Wilcoxon SRT table for either the "baseline" or "consecutive" comparison.[required]

Examples¶

wilcoxon_baseline0¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'timedist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'

qiime stats wilcoxon-srt \
  --i-distribution timedist.qza \
  --p-compare baseline \
  --p-baseline-group 0 \
  --p-p-val-approx asymptotic \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn = 'timedist.qza'
request.urlretrieve(url, fn)
timedist = Artifact.load(fn)

stats, = stats_actions.wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/wilcoxon-srt/1/timedist.qza'
fn <- 'timedist.qza'
request$urlretrieve(url, fn)
timedist <- Artifact$load(fn)

action_results <- stats_actions$wilcoxon_srt(
    distribution=timedist,
    compare='baseline',
    baseline_group='0',
    p_val_approx='asymptotic',
)
stats <- action_results$stats

timedist.qza | download | view
stats.qza | download | view

Facets a distribution into independent distributions where each facet is an inner slice from the outer group.

Inputs¶

distribution: Dist1D[Multi | NestedOrdered | NestedUnordered, Matched | Independent]: A nested or multi Dist1D which will be partitioned into undordered and independent subgroups.[required]

Outputs¶

distributions: Collection[Dist1D[Unordered, Independent]]: A collection of unordered and independent Dist1Ds.[required]

Facet a distribution into per-class/level distributions where each facet preserves the outer group structure.

Inputs¶

distribution: Dist1D[NestedOrdered¹ | NestedUnordered², Independent¹ | Matched²]: A nested Dist1D which will be partitioned into non-nested Dist1D[required]

Outputs¶

distributions: Collection[Dist1D[Ordered¹ | Unordered², Independent¹ | Matched²]]: A collection of non-nested Dist1Ds[required]

stats collate-stats¶

Converts a collection of stats tables into a single table

Inputs¶

tables: Collection[StatsTable[Pairwise]]: <no description>[required]

Outputs¶

table: StatsTable[Pairwise]: <no description>[required]

stats prep-alpha-distribution¶

Alpha diversity to Dist1D

Inputs¶

alpha_diversity: SampleData[AlphaDiversity]: Alpha diversity which will become the "measure"[required]

Parameters¶

metadata: Metadata: Sample metadata to use[required]
columns: List[Str]: Columns to include as group information[required]
subject: Str % Choices('') | Str | Str % Choices('') | Str: If provided, will cause the Dist1D to be matched for repeated measures.[default: '']
timepoint: Str % Choices('') | Str % Choices('') | Str | Str: If provided, will cause the Dist1D to be stratified by timepoint. Required if using subject.[default: '']

Outputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[Multi, Matched] | Dist1D[NestedOrdered, Independent] | Dist1D[NestedOrdered, Matched]: The resulting Dist1D.[required]

stats plot-rainclouds¶

Plot raincloud distributions for each group.

Inputs¶

data: Dist1D[Multi | Ordered | Unordered | NestedOrdered | NestedUnordered, Matched | Independent]: The group distributions to plot.[required]
stats: StatsTable[Pairwise]: Statistical tests to display.[optional]

Outputs¶

visualization: Visualization: <no description>[required]

Examples¶

plot_rainclouds¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'

qiime stats plot-rainclouds \
  --i-data dist.qza \
  --o-visualization raincloud-plot.qzv

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

raincloud_plot_viz, = stats_actions.plot_rainclouds(
    data=dist,
)

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: dist.qza
2. In the larger text-area, copy-and-paste: https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza
3. ("Type", "Genome", and "Settings" can be ignored)
Press the Start button at the bottom.

Using the qiime2 stats plot-rainclouds tool:

Set "data" to #: dist.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 stats plot-rainclouds [...] : visualization.qzv`	`raincloud-plot.qzv`

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/plot-rainclouds/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$plot_rainclouds(
    data=dist,
)
raincloud_plot_viz <- action_results$visualization

dist.qza | download | view
raincloud-plot.qzv | download | view

Citations¶

Inputs¶

distribution: Dist1D[Multi, Independent] | Dist1D[NestedOrdered | NestedUnordered, Matched] | Dist1D[NestedOrdered | NestedUnordered, Independent]: <no description>[required]

Parameters¶

facet: Str % Choices('within') | Str % Choices('within') | Str % Choices('within', 'across'): Whether to facet within or across the outer group.[default: 'within']

Outputs¶

stats: StatsTable[Pairwise]: <no description>[required]

Examples¶

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet across \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/1/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='across',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

[Command Line]

[Python API]

[Galaxy]

[R API]

[View Source]

wget -O 'dist.qza' \
  'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'

qiime stats mann-whitney-u-facet \
  --i-distribution dist.qza \
  --p-facet within \
  --o-stats stats.qza

from qiime2 import Artifact
from urllib import request
import qiime2.plugins.stats.actions as stats_actions

url = 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn = 'dist.qza'
request.urlretrieve(url, fn)
dist = Artifact.load(fn)

stats, = stats_actions.mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)

library(reticulate)

Artifact <- import("qiime2")$Artifact
request <- import("urllib")$request
stats_actions <- import("qiime2.plugins.stats.actions")

url <- 'https://amplicon-docs.qiime2.org/en/latest/data/examples/stats/mann-whitney-u-facet/2/dist.qza'
fn <- 'dist.qza'
request$urlretrieve(url, fn)
dist <- Artifact$load(fn)

action_results <- stats_actions$mann_whitney_u_facet(
    distribution=dist,
    facet='within',
)
stats <- action_results$stats

dist.qza | download | view
stats.qza | download | view

Citations¶