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comparison qiime2/qiime_feature-classifier_classify-sklearn.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_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn" version="2019.4">
3 <description> - Pre-fitted sklearn-based taxonomy classifier</description>
4 <requirements>
5 <requirement type="package" version="2019.4">qiime2</requirement>
6 </requirements>
7 <command><![CDATA[
8 qiime feature-classifier classify-sklearn
9
10 --i-reads=$ireads
11 --i-classifier=$iclassifier
12
13 #set $pnjobs = '${GALAXY_SLOTS:-4}'
14
15 #if str($pnjobs):
16 --p-n-jobs="$pnjobs"
17 #end if
18
19
20 #if $pconfidence:
21 --p-confidence=$pconfidence
22 #end if
23
24 #if str($preadorientation) != 'None':
25 --p-read-orientation=$preadorientation
26 #end if
27
28 --o-classification=oclassification
29 ;
30 cp oclassification.qza $oclassification
31 ]]></command>
32 <inputs>
33 <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data"/>
34 <param format="qza,no_unzip.zip" label="--i-classifier: ARTIFACT TaxonomicClassifier The taxonomic classifier for classifying the reads. [required]" name="iclassifier" optional="False" type="data"/>
35 <param label="--p-confidence: NUMBER Confidence threshold for limiting taxonomic depth. Provide -1 to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments. [default: 0.7]" name="pconfidence" optional="True" type="float" value="0.7"/>
36 <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select">
37 <option selected="True" value="None">Selection is Optional</option>
38 <option value="same">same</option>
39 <option value="reverse-complement">reverse-complement</option>
40 </param>
41 </inputs>
42 <outputs>
43 <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification"/>
44 </outputs>
45 <help><![CDATA[
46 Pre-fitted sklearn-based taxonomy classifier
47 ############################################
48
49 Classify reads by taxon using a fitted classifier.
50
51 Parameters
52 ----------
53 reads : FeatureData[Sequence]
54 The feature data to be classified.
55 classifier : TaxonomicClassifier
56 The taxonomic classifier for classifying the reads.
57 reads_per_batch : Int % Range(0, None), optional
58 Number of reads to process in each batch. If 0, this parameter is
59 autoscaled to min( number of query sequences / n_jobs, 20000).
60 pre_dispatch : Str, optional
61 "all" or expression, as in "3*n_jobs". The number of batches (of tasks)
62 to be pre-dispatched.
63 confidence : Float, optional
64 Confidence threshold for limiting taxonomic depth. Provide -1 to
65 disable confidence calculation, or 0 to calculate confidence but not
66 apply it to limit the taxonomic depth of the assignments.
67 read_orientation : Str % Choices('same', 'reverse-complement'), optional
68 Direction of reads with respect to reference sequences. same will cause
69 reads to be classified unchanged; reverse-complement will cause reads
70 to be reversed and complemented prior to classification. Default is to
71 autodetect based on the confidence estimates for the first 100 reads.
72
73 Returns
74 -------
75 classification : FeatureData[Taxonomy]
76 ]]></help>
77 <macros>
78 <import>qiime_citation.xml</import>
79 </macros>
80 <expand macro="qiime_citation"/>
81 </tool>