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"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit a1ad1ddd9b8e4db5bb82c3accae8311e0e488b19"
author ebi-gxa
date Fri, 27 Nov 2020 13:46:23 +0000
parents 33fa4949e080
children
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1 <tool id="scpred_train_model" name="Scpred train" version="@TOOL_VERSION@+galaxy0" profile="@PROFILE@">
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2 <description>Train classification model</description>
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3 <macros>
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4 <import>scpred_macros.xml</import>
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5 </macros>
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6 <expand macro="requirements" />
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7 <command detect_errors="exit_code"><![CDATA[
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8 scpred_train_model.R --input-object "${input_object}" --model "${model}" --output-path "${output_obj_path}" --iter-num "${iter_num}" --num-cores \${GALAXY_SLOTS:-1} --tune-length "${tune_length}" --metric "${metric}" --preprocess "${preprocess}" --return-data "${return_data}" --save-predictions "${save_predictions}"
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10 #if $train_id
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11 --train-id '${train_id}'
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12 #end if
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13 #if $resample_method
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14 --resample-method '${resample_method}'
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15 #end if
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16 #if $reclassify
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17 --reclassify "${reclassify}"
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18 #end if
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19
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20 ]]></command>
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21 <inputs>
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22
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23 <param type="data" name="input_object" label="Input SCE object" format="rdata" help="Input SCE object in .rds format"/>
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24 <param type="text" name="train_id" optional="true" label="Dataset ID" help="ID of the training dataset" />
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25 <param type="text" name="model" label="Model type to train" value="svmRadial" help="Model type used for training. Must be one of the models supported by Caret package. Default: svmRadial" />
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26 <param type="text" name="resample_method" optional="true" value="cv" label="Resample Method" help="Resampling method used for model fit evaluation" />
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27 <param type="integer" name="iter_num" optional="true" value="5" label="Number of Iterations" help="Number of resampling iterations. Default: 5" />
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28 <param type="integer" name="tune_length" optional="true" value="3" label="Tune Length" help="An integer denoting the amount of granularity in the tuning parameter grid" />
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29 <param type="text" name="metric" optional="true" value="ROC,PR,Accuracy,Kappa" label="Performance Metric" help="Performance metric to be used to select best model" />
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30 <param type="text" name="preprocess" optional="true" value="center,scale" label="Pre-processing Method" help="A string vector that defines a pre-processing of the predictor data. Enter values as comma-separated string. Current possibilities are 'BoxCox', 'YeoJohnson', 'expoTrans', 'center', 'scale', 'range', 'knnImpute', 'bagImpute', 'medianImpute', 'pca', 'ica' and 'spatialSign'. The default is 'center' and 'scale'." />
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31 <param type="boolean" checked="false" name="return_data" label="Return Data" help="If TRUE, training data is returned within scPred object. Default: False"/>
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32 <param type="text" name="save_predictions" optional="true" value="final" label="Save Predictions" help="Specifies the set of hold-out predictions for each resample that should be returned. Values can be either 'all', 'final' or 'none'." />
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33 <param type="text" name="reclassify" optional="true" label="Cells to Reclassify" help="Cell types to reclassify using a different model" />
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34
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35 </inputs>
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36 <outputs>
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37 <data name="output_obj_path" format="rdata" />
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38 </outputs>
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39 <tests>
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40 <test>
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41 <param name="input_object" value="scPred_feat_space.rds" />
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42 <param name="train_id" value="E-ENAD-16" />
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43 <output name="output_obj_path" file="scPred_trained.rds" compare="sim_size" delta="10000000"/>
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44 </test>
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45 </tests>
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46 <help><![CDATA[
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47 @HELP@
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48
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49 @VERSION_HISTORY@
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50 ]]></help>
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51 <expand macro="citations" />
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52 </tool>