view qiime2__vsearch__cluster_features_de_novo.xml @ 3:a7e23c72f344 draft default tip

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__vsearch commit 389df0134cd0763dcf02aac6e623fc15f8861c1e
author q2d2
date Thu, 25 Apr 2024 21:27:48 +0000
parents 397c1be954c2
children
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<?xml version='1.0' encoding='utf-8'?>
<!--
Copyright (c) 2024, QIIME 2 development team.

Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)
-->
<!--
This tool was automatically generated by:
    q2galaxy (version: 2024.2.1)
for:
    qiime2 (version: 2024.2.0)
-->
<tool name="qiime2 vsearch cluster-features-de-novo" id="qiime2__vsearch__cluster_features_de_novo" version="2024.2.0+q2galaxy.2024.2.1" profile="22.05" license="BSD-3-Clause">
    <description>De novo clustering of features.</description>
    <requirements>
        <container type="docker">quay.io/qiime2/amplicon:2024.2</container>
    </requirements>
    <version_command>q2galaxy version vsearch</version_command>
    <command detect_errors="exit_code">q2galaxy run vsearch cluster_features_de_novo '$inputs'</command>
    <configfiles>
        <inputs name="inputs" data_style="staging_path_and_source_path"/>
    </configfiles>
    <inputs>
        <param name="sequences" type="data" format="qza" label="sequences: FeatureData[Sequence]" help="[required]  The sequences corresponding to the features in table.">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureData[Sequence]"/>
            </options>
            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureData[Sequence]']</validator>
        </param>
        <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency]" help="[required]  The feature table to be clustered.">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureTable[Frequency]"/>
            </options>
            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Frequency]']</validator>
        </param>
        <param name="perc_identity" type="float" min="1e-06" max="1" value="" label="perc_identity: Float % Range(0, 1, inclusive_start=False, inclusive_end=True)" help="[required]  The percent identity at which clustering should be performed. This parameter maps to vsearch's --id parameter."/>
        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
            <param name="strand" type="select" label="strand: Str % Choices('plus', 'both')" display="radio">
                <option value="plus" selected="true">plus</option>
                <option value="both">both</option>
            </param>
        </section>
    </inputs>
    <outputs>
        <data name="clustered_table" format="qza" label="${tool.name} on ${on_string}: clustered_table.qza" from_work_dir="clustered_table.qza"/>
        <data name="clustered_sequences" format="qza" label="${tool.name} on ${on_string}: clustered_sequences.qza" from_work_dir="clustered_sequences.qza"/>
    </outputs>
    <tests/>
    <help>
QIIME 2: vsearch cluster-features-de-novo
=========================================
De novo clustering of features.


Outputs:
--------
:clustered_table.qza: The table following clustering of features.
:clustered_sequences.qza: Sequences representing clustered features.

|  

Description:
------------
Given a feature table and the associated feature sequences, cluster the features based on user-specified percent identity threshold of their sequences. This is not a general-purpose de novo clustering method, but rather is intended to be used for clustering the results of quality-filtering/dereplication methods, such as DADA2, or for re-clustering a FeatureTable at a lower percent identity than it was originally clustered at. When a group of features in the input table are clustered into a single feature, the frequency of that single feature in a given sample is the sum of the frequencies of the features that were clustered in that sample. Feature identifiers and sequences will be inherited from the centroid feature of each cluster. See the vsearch documentation for details on how sequence clustering is performed.


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</help>
    <citations>
        <citation type="doi">10.7717/peerj.2584</citation>
        <citation type="doi">10.1038/s41587-019-0209-9</citation>
    </citations>
</tool>