Mercurial > repos > florianbegusch > qiime2_suite
view qiime2/qiime_sample-classifier_predict-classification.xml @ 0:370e0b6e9826 draft
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author | florianbegusch |
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date | Wed, 17 Jul 2019 03:05:17 -0400 |
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children | f190567fe3f6 |
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<?xml version="1.0" ?> <tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification" version="2019.4"> <description> - Use trained classifier to predict target values for new samples.</description> <requirements> <requirement type="package" version="2019.4">qiime2</requirement> </requirements> <command><![CDATA[ qiime sample-classifier predict-classification --i-table=$itable --i-sample-estimator=$isampleestimator #set $pnjobs = '${GALAXY_SLOTS:-4}' #if str($pnjobs): --p-n-jobs="$pnjobs" #end if --o-predictions=opredictions ; cp opredictions.qza $opredictions ]]></command> <inputs> <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data"/> <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data"/> </inputs> <outputs> <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions"/> </outputs> <help><![CDATA[ Use trained classifier to predict target values for new samples. ################################################################ Use trained estimator to predict target values for new samples. These will typically be unseen samples, e.g., test data (derived manually or from split_table) or samples with unknown values, but can theoretically be any samples present in a feature table that contain overlapping features with the feature table used to train the estimator. Parameters ---------- table : FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. sample_estimator : SampleEstimator[Classifier] Sample classifier trained with fit_classifier. Returns ------- predictions : SampleData[ClassifierPredictions] Predicted target values for each input sample. ]]></help> <macros> <import>qiime_citation.xml</import> </macros> <expand macro="qiime_citation"/> </tool>