0
|
1 <?xml version="1.0" ?>
|
9
|
2 <tool id="qiime_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn" version="2019.7">
|
0
|
3 <description> - Pre-fitted sklearn-based taxonomy classifier</description>
|
|
4 <requirements>
|
9
|
5 <requirement type="package" version="2019.7">qiime2</requirement>
|
0
|
6 </requirements>
|
|
7 <command><![CDATA[
|
|
8 qiime feature-classifier classify-sklearn
|
|
9
|
6
|
10
|
|
11 #if str( $id_to_classifier_fp.selector ) == 'history'
|
|
12 #set $classifier = $id_to_classifier_fp.classifier_fp
|
|
13 --i-classifier '$classifier'
|
|
14 #else:
|
|
15 #set $classifier = $id_to_classifier_fp.classifier_fp.fields.path
|
|
16 --i-classifier '$classifier'
|
|
17 #end if
|
|
18
|
|
19
|
0
|
20 --i-reads=$ireads
|
|
21
|
|
22 #set $pnjobs = '${GALAXY_SLOTS:-4}'
|
|
23
|
|
24 #if str($pnjobs):
|
|
25 --p-n-jobs="$pnjobs"
|
|
26 #end if
|
|
27
|
|
28
|
6
|
29 #if str($pconfidence) != '':
|
|
30 #if float($pconfidence) >= 0.0:
|
|
31 --p-confidence=$pconfidence
|
|
32 #end if
|
0
|
33 #end if
|
|
34
|
|
35 #if str($preadorientation) != 'None':
|
|
36 --p-read-orientation=$preadorientation
|
|
37 #end if
|
|
38
|
|
39 --o-classification=oclassification
|
|
40 ;
|
|
41 cp oclassification.qza $oclassification
|
|
42 ]]></command>
|
|
43 <inputs>
|
6
|
44 <conditional name="id_to_classifier_fp" optional="True">
|
|
45 <param name="selector" type="select" label="Reference classifier to query">
|
|
46 <option value="cached">Public classifiers</option>
|
|
47 <option value="history">Classifiers from your history</option>
|
|
48 </param>
|
|
49 <when value="cached">
|
|
50 <param name="classifier_fp" label="Reference classifier" type="select" optional="True">
|
|
51 <options from_data_table="qiime_rep_set" />
|
|
52 </param>
|
|
53 </when>
|
|
54 <when value="history">
|
|
55 <param name="classifier_fp" type="data" format="qza,no_unzip.zip" label="Reference classifier" optional="True" />
|
|
56 </when>
|
|
57 </conditional>
|
|
58
|
0
|
59 <param format="qza,no_unzip.zip" label="--i-reads: ARTIFACT FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data"/>
|
|
60 <param label="--p-confidence: NUMBER Confidence threshold for limiting taxonomic depth. Provide -1 to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments. [default: 0.7]" name="pconfidence" optional="True" type="float" value="0.7"/>
|
|
61 <param label="--p-read-orientation: " name="preadorientation" optional="True" type="select">
|
|
62 <option selected="True" value="None">Selection is Optional</option>
|
|
63 <option value="same">same</option>
|
|
64 <option value="reverse-complement">reverse-complement</option>
|
|
65 </param>
|
|
66 </inputs>
|
|
67 <outputs>
|
|
68 <data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification"/>
|
|
69 </outputs>
|
|
70 <help><![CDATA[
|
|
71 Pre-fitted sklearn-based taxonomy classifier
|
|
72 ############################################
|
|
73
|
|
74 Classify reads by taxon using a fitted classifier.
|
|
75
|
|
76 Parameters
|
|
77 ----------
|
|
78 reads : FeatureData[Sequence]
|
|
79 The feature data to be classified.
|
|
80 classifier : TaxonomicClassifier
|
|
81 The taxonomic classifier for classifying the reads.
|
|
82 reads_per_batch : Int % Range(0, None), optional
|
|
83 Number of reads to process in each batch. If 0, this parameter is
|
|
84 autoscaled to min( number of query sequences / n_jobs, 20000).
|
|
85 pre_dispatch : Str, optional
|
|
86 "all" or expression, as in "3*n_jobs". The number of batches (of tasks)
|
|
87 to be pre-dispatched.
|
|
88 confidence : Float, optional
|
|
89 Confidence threshold for limiting taxonomic depth. Provide -1 to
|
|
90 disable confidence calculation, or 0 to calculate confidence but not
|
|
91 apply it to limit the taxonomic depth of the assignments.
|
|
92 read_orientation : Str % Choices('same', 'reverse-complement'), optional
|
|
93 Direction of reads with respect to reference sequences. same will cause
|
|
94 reads to be classified unchanged; reverse-complement will cause reads
|
|
95 to be reversed and complemented prior to classification. Default is to
|
|
96 autodetect based on the confidence estimates for the first 100 reads.
|
|
97
|
|
98 Returns
|
|
99 -------
|
|
100 classification : FeatureData[Taxonomy]
|
|
101 ]]></help>
|
|
102 <macros>
|
|
103 <import>qiime_citation.xml</import>
|
|
104 </macros>
|
|
105 <expand macro="qiime_citation"/>
|
|
106 </tool>
|