Mercurial > repos > florianbegusch > qiime2_suite_zmf
comparison qiime2-2020.8/qiime_sample-classifier_predict-classification.xml @ 0:5c352d975ef7 draft
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author | florianbegusch |
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date | Thu, 03 Sep 2020 09:33:04 +0000 |
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1 <?xml version="1.0" ?> | |
2 <tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification" | |
3 version="2020.8"> | |
4 <description>Use trained classifier to predict target values for new samples.</description> | |
5 <requirements> | |
6 <requirement type="package" version="2020.8">qiime2</requirement> | |
7 </requirements> | |
8 <command><![CDATA[ | |
9 qiime sample-classifier predict-classification | |
10 | |
11 --i-table=$itable | |
12 | |
13 --i-sample-estimator=$isampleestimator | |
14 | |
15 --p-n-jobs=$pnjobs | |
16 | |
17 --o-predictions=opredictions | |
18 | |
19 --o-probabilities=oprobabilities | |
20 | |
21 #if str($examples) != 'None': | |
22 --examples=$examples | |
23 #end if | |
24 | |
25 ; | |
26 cp oprobabilities.qza $oprobabilities | |
27 | |
28 ]]></command> | |
29 <inputs> | |
30 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" /> | |
31 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data" /> | |
32 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> | |
33 | |
34 </inputs> | |
35 | |
36 <outputs> | |
37 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" /> | |
38 <data format="qza" label="${tool.name} on ${on_string}: probabilities.qza" name="oprobabilities" /> | |
39 | |
40 </outputs> | |
41 | |
42 <help><![CDATA[ | |
43 Use trained classifier to predict target values for new samples. | |
44 ############################################################### | |
45 | |
46 Use trained estimator to predict target values for new samples. These will | |
47 typically be unseen samples, e.g., test data (derived manually or from | |
48 split_table) or samples with unknown values, but can theoretically be any | |
49 samples present in a feature table that contain overlapping features with | |
50 the feature table used to train the estimator. | |
51 | |
52 Parameters | |
53 ---------- | |
54 table : FeatureTable[Frequency] | |
55 Feature table containing all features that should be used for target | |
56 prediction. | |
57 sample_estimator : SampleEstimator[Classifier] | |
58 Sample classifier trained with fit_classifier. | |
59 n_jobs : Int, optional | |
60 Number of jobs to run in parallel. | |
61 | |
62 Returns | |
63 ------- | |
64 predictions : SampleData[ClassifierPredictions] | |
65 Predicted target values for each input sample. | |
66 probabilities : SampleData[Probabilities] | |
67 Predicted class probabilities for each input sample. | |
68 ]]></help> | |
69 <macros> | |
70 <import>qiime_citation.xml</import> | |
71 </macros> | |
72 <expand macro="qiime_citation"/> | |
73 </tool> |