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comparison qiime2/qiime_vsearch_cluster-features-de-novo.xml @ 0:370e0b6e9826 draft

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author florianbegusch
date Wed, 17 Jul 2019 03:05:17 -0400
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1 <?xml version="1.0" ?>
2 <tool id="qiime_vsearch_cluster-features-de-novo" name="qiime vsearch cluster-features-de-novo" version="2019.4">
3 <description> - De novo clustering of features.</description>
4 <requirements>
5 <requirement type="package" version="2019.4">qiime2</requirement>
6 </requirements>
7 <command><![CDATA[
8 qiime vsearch cluster-features-de-novo
9
10 --i-sequences=$isequences
11 --i-table=$itable
12 --p-perc-identity="$ppercidentity"
13
14 #set $pthreads = '${GALAXY_SLOTS:-4}'
15 #if str($pthreads):
16 --p-threads="$pthreads"
17 #end if
18
19 --o-clustered-table=oclusteredtable
20 --o-clustered-sequences=oclusteredsequences
21 ;
22 cp oclusteredtable.qza $oclusteredtable;
23 cp oclusteredsequences.qza $oclusteredsequences
24 ]]></command>
25 <inputs>
26 <param format="qza,no_unzip.zip" label="--i-sequences: ARTIFACT FeatureData[Sequence] The sequences corresponding to the features in table. [required]" name="isequences" optional="False" type="data"/>
27 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] The feature table to be clustered. [required]" name="itable" optional="False" type="data"/>
28
29 <param label="--p-perc-identity: PROPORTION Range(0, 1, inclusive_start=False, inclusive_end=True) The percent identity at which clustering should be performed. This parameter maps to vsearch's --id parameter. [required]" name="ppercidentity" optional="False" min="0" max="1" value="" exclude_min="True" exclude_max="False" type="float"/>
30 </inputs>
31 <outputs>
32 <data format="qza" label="${tool.name} on ${on_string}: clusteredtable.qza" name="oclusteredtable"/>
33 <data format="qza" label="${tool.name} on ${on_string}: clusteredsequences.qza" name="oclusteredsequences"/>
34 </outputs>
35 <help><![CDATA[
36 De novo clustering of features.
37 ###############################
38
39 Given a feature table and the associated feature sequences, cluster the
40 features based on user-specified percent identity threshold of their
41 sequences. This is not a general-purpose de novo clustering method, but
42 rather is intended to be used for clustering the results of quality-
43 filtering/dereplication methods, such as DADA2, or for re-clustering a
44 FeatureTable at a lower percent identity than it was originally clustered
45 at. When a group of features in the input table are clustered into a single
46 feature, the frequency of that single feature in a given sample is the sum
47 of the frequencies of the features that were clustered in that sample.
48 Feature identifiers and sequences will be inherited from the centroid
49 feature of each cluster. See the vsearch documentation for details on how
50 sequence clustering is performed.
51
52 Parameters
53 ----------
54 sequences : FeatureData[Sequence]
55 The sequences corresponding to the features in table.
56 table : FeatureTable[Frequency]
57 The feature table to be clustered.
58 perc_identity : Float % Range(0, 1, inclusive_start=False, inclusive_end=True)
59 The percent identity at which clustering should be performed. This
60 parameter maps to vsearch's --id parameter.
61 Returns
62 -------
63 clustered_table : FeatureTable[Frequency]
64 The table following clustering of features.
65 clustered_sequences : FeatureData[Sequence]
66 Sequences representing clustered features.
67 ]]></help>
68 <macros>
69 <import>qiime_citation.xml</import>
70 </macros>
71 <expand macro="qiime_citation"/>
72 </tool>