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comparison qiime2/qiime_vsearch_cluster-features-de-novo.xml @ 29:3ba9833030c1 draft

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author florianbegusch
date Fri, 04 Sep 2020 13:12:49 +0000
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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"
3 version="2020.8">
4 <description>De novo clustering of features.</description>
5 <requirements>
6 <requirement type="package" version="2020.8">qiime2</requirement>
7 </requirements>
8 <command><![CDATA[
9 qiime vsearch cluster-features-de-novo
10
11 --i-sequences=$isequences
12
13 --i-table=$itable
14
15 --p-perc-identity=$ppercidentity
16
17 --p-threads=$pthreads
18
19 --o-clustered-table=oclusteredtable
20
21 --o-clustered-sequences=oclusteredsequences
22
23 #if str($examples) != 'None':
24 --examples=$examples
25 #end if
26
27 ;
28 cp oclusteredsequences.qza $oclusteredsequences
29
30 ]]></command>
31 <inputs>
32 <param format="qza,no_unzip.zip" label="--i-sequences: ARTIFACT FeatureData[Sequence] The sequences corresponding to the features in table. [required]" name="isequences" optional="False" type="data" />
33 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] The feature table to be clustered. [required]" name="itable" optional="False" type="data" />
34 <param label="--p-perc-identity: PROPORTION Range(0, 1, inclusive_start=False, inclusive_end=True) The percent identity at which clustering should be performed. This parameter maps to vsearch\'s --id parameter. [required]" name="ppercidentity" optional="False" type="text" />
35 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
36
37 </inputs>
38
39 <outputs>
40 <data format="qza" label="${tool.name} on ${on_string}: clusteredtable.qza" name="oclusteredtable" />
41 <data format="qza" label="${tool.name} on ${on_string}: clusteredsequences.qza" name="oclusteredsequences" />
42
43 </outputs>
44
45 <help><![CDATA[
46 De novo clustering of features.
47 ###############################################################
48
49 Given a feature table and the associated feature sequences, cluster the
50 features based on user-specified percent identity threshold of their
51 sequences. This is not a general-purpose de novo clustering method, but
52 rather is intended to be used for clustering the results of quality-
53 filtering/dereplication methods, such as DADA2, or for re-clustering a
54 FeatureTable at a lower percent identity than it was originally clustered
55 at. When a group of features in the input table are clustered into a single
56 feature, the frequency of that single feature in a given sample is the sum
57 of the frequencies of the features that were clustered in that sample.
58 Feature identifiers and sequences will be inherited from the centroid
59 feature of each cluster. See the vsearch documentation for details on how
60 sequence clustering is performed.
61
62 Parameters
63 ----------
64 sequences : FeatureData[Sequence]
65 The sequences corresponding to the features in table.
66 table : FeatureTable[Frequency]
67 The feature table to be clustered.
68 perc_identity : Float % Range(0, 1, inclusive_start=False, inclusive_end=True)
69 The percent identity at which clustering should be performed. This
70 parameter maps to vsearch's --id parameter.
71 threads : Int % Range(0, 256, inclusive_end=True), optional
72 The number of threads to use for computation. Passing 0 will launch one
73 thread per CPU core.
74
75 Returns
76 -------
77 clustered_table : FeatureTable[Frequency]
78 The table following clustering of features.
79 clustered_sequences : FeatureData[Sequence]
80 Sequences representing clustered features.
81 ]]></help>
82 <macros>
83 <import>qiime_citation.xml</import>
84 </macros>
85 <expand macro="qiime_citation"/>
86 </tool>