q2-alignment

This QIIME 2 plugin provides support for generating and manipulating sequence alignments.

version: 2026.4.0

website: https://github.com/qiime2/q2-alignment

user support:

Please post to the QIIME 2 forum for help with this plugin: https://forum.qiime2.org

Actions¶

alignment mafft¶

Perform de novo multiple sequence alignment using MAFFT.

Citations¶

Katoh & Standley, 2013

Inputs¶

sequences: FeatureData[Sequence] | FeatureData[ProteinSequence]

The sequences to be aligned.[required]

Parameters¶

n_threads: Threads

The number of threads. (Use auto to automatically use all available cores)[default: 1]

parttree: Bool

This flag is required if the number of sequences being aligned are larger than 1,000,000. Disabled by default.[default: False]

large: Bool

This flag is required when aligning very large datasets that do not otherwise fit into memory. Temporary data is then stored in files, instead of RAM. The --use-cache flag specifies the storage location of the temporary files created. By default, $TMP/qiime2/ is used.[default: False]

strategy: Str % Choices('auto', 'genafpair', 'globalpair', 'localpair', 'nofft')

Specifies the multiple alignment strategy to use. Exactly one strategy may be specified. Valid options are: 'auto', 'nofft', 'globalpair', 'localpair', and 'genafpair'. Default strategy: FFT-NS.[optional]

maxiterate: Int % Range(0, None)

Specifies how many iterative refinement cycles are performed after the initial progressive alignment. By default, no iterative refinement is performed.[optional]

retree: Int % Range(0, None)

Specifies the number of times the guide tree is rebuilt during the progressive stage. Typically, tree topology stabilizes after 2-3 iterations and higher values rarely improves alignment quality enough to justify the extra computation.[optional]

Outputs¶

alignment: FeatureData[AlignedSequence] | FeatureData[AlignedProteinSequence]

The aligned sequences.[required]

alignment mafft-add¶

Add new sequences to an existing alignment with MAFFT.

Citations¶

Katoh & Standley, 2013

Inputs¶

alignment: FeatureData[AlignedSequence] | FeatureData[AlignedProteinSequence]

The alignment to which sequences should be added.[required]

sequences: FeatureData[Sequence] | FeatureData[ProteinSequence]

The sequences to be added.[required]

Parameters¶

n_threads: Threads

The number of threads. (Use auto to automatically use all available cores)[default: 1]

parttree: Bool

This flag is required if the number of sequences being aligned are larger than 1,000,000. Disabled by default.[default: False]

addfragments: Bool

Optimize for the addition of short sequence fragments (for example, primer or amplicon sequences). If not set, default sequence addition is used.[default: False]

keeplength: Bool

If selected, the alignment length will be unchanged. Any added sequence that would otherwise introduce new insertions into the alignment, will have those insertions deleted, to preserve original alignment length.[default: False]

large: Bool

This flag is required when aligning very large datasets that do not otherwise fit into memory. Temporary data is then stored in files, instead of RAM. The --use-cache flag specifies the storage location of the temporary files created. By default, $TMP/qiime2/ is used.[default: False]

strategy: Str % Choices('auto', 'genafpair', 'globalpair', 'localpair', 'nofft')

Specifies the multiple alignment strategy to use. Exactly one strategy may be specified. Valid options are: 'auto', 'nofft', 'globalpair', 'localpair', and 'genafpair'. Default strategy: FFT-NS.[optional]

maxiterate: Int % Range(0, None)

Specifies how many iterative refinement cycles are performed after the initial progressive alignment. By default, no iterative refinement is performed.[optional]

retree: Int % Range(0, None)

Specifies the number of times the guide tree is rebuilt during the progressive stage. Typically, tree topology stabilizes after 2-3 iterations and higher values rarely improves alignment quality enough to justify the extra computation.[optional]

Outputs¶

expanded_alignment: FeatureData[AlignedSequence] | FeatureData[AlignedProteinSequence]

Alignment containing the provided aligned and unaligned sequences.[required]

alignment mask¶

Mask (i.e., filter) unconserved and highly gapped columns from an alignment. Default min_conservation was chosen to reproduce the mask presented in Lane (1991).

Citations¶

Lane, 1991

Inputs¶

alignment: FeatureData[AlignedSequence] | FeatureData[AlignedProteinSequence]

The alignment to be masked.[required]

Parameters¶

max_gap_frequency: Float % Range(0, 1, inclusive_end=True)

The maximum relative frequency of gap characters in a column for the column to be retained. This relative frequency must be a number between 0.0 and 1.0 (inclusive), where 0.0 retains only those columns without gap characters, and 1.0 retains all columns regardless of gap character frequency.[default: 1.0]

min_conservation: Float % Range(0, 1, inclusive_end=True)

The minimum relative frequency of at least one non-gap character in a column for that column to be retained. This relative frequency must be a number between 0.0 and 1.0 (inclusive). For example, if a value of 0.4 is provided, a column will only be retained if it contains at least one character that is present in at least 40% of the sequences.[default: 0.4]

Outputs¶

masked_alignment: FeatureData[AlignedSequence] | FeatureData[AlignedProteinSequence]

The masked alignment.[required]

alignment trim-alignment¶

Trim an existing alignment based on provided primers or specific, pre-defined positions. Primers take precedence over the positions,i.e. if both are provided, positions will be ignored.When using primers in combination with a DNA alignment, a new alignment will be generated to locate primer positions. Subsequently, start (5'-most) and end (3'-most) position from fwd and rev primer located within the new alignment is identified and used for slicing the original alignment. The retention of alignment positions that span the primer locations can be toggled. WARNING: finding alignment positions via primer search can be inefficient for very large alignments and is only recommended for small alignments. For large alignments providing specific alignment positions is ideal.

Citations¶

Robeson et al., 2021

Inputs¶

aligned_sequences: FeatureData[AlignedSequence]

Aligned DNA sequences.[required]

Parameters¶

primer_fwd: Str

Forward primer used to find the start position for alignment trimming. Provide as 5'-3'.[optional]

primer_rev: Str

Reverse primer used to find the end position for alignment trimming. Provide as 5'-3'.[optional]

position_start: Int % Range(1, None)

Position within the alignment where the trimming will begin. If not provided, alignment will not be trimmed at the beginning. If forward primer isspecified this parameter will be ignored.[optional]

position_end: Int % Range(1, None)

Position within the alignment where the trimming will end. If not provided, alignment will not be trimmed at the end. If reverse primer is specified this parameter will be ignored.[optional]

keep_primer_location: Bool

Retain the alignment positions of the primer binding location. Note: the primers themselves will be removed, but the alignment positions where the primers align will be retained in the alignment.[default: False]

n_threads: Int % Range(1, None)

Number of threads to use for primer-based trimming, otherwise ignored. (Use auto to automatically use all available cores)[default: 1]

Outputs¶

trimmed_sequences: FeatureData[AlignedSequence]

Trimmed sequence alignment.[required]