comparison scpred_get_feature_space.xml @ 5:17325882fa72 draft default tip

"planemo upload for repository https://github.com/ebi-gene-expression-group/container-galaxy-sc-tertiary/ commit a1ad1ddd9b8e4db5bb82c3accae8311e0e488b19"

4:826f41212307

    <macros>
         <import>scpred_macros.xml</import>
    </macros>
    <expand macro='requirements' />
    <command detect_errors='exit_code'><![CDATA[
        scpred_get_feature_space.R  --input-object '${input_object}'  --prediction-column '${prediction_column}'  --output-path '${output_obj_path}' 

        #if $explained_var_limit
        --explained-var-limit '${explained_var_limit}'
        #end if
        #if $eigenvalue_plot_path
        --eigenvalue-plot-path '${eigenvalue_plot_path}'
        #end if
        ]]></command>
    <inputs>
        <param type='data' name='input_object' label='Input SCE object' format='rdata' help='Input SCE object in .rds format' />
        <param type='text' name='prediction_column' label='Prediction column' help='Name of the metadata column that contains training labels' />
        <param type='float' name='explained_var_limit' label='Limit of explained variance' value="0.01" help='Threshold to filter principal components based on variance explained' />
    </inputs>
    <outputs>
        <data name='output_obj_path' format='rdata' />
        <data name='eigenvalue_plot_path' format='png' />
    </outputs>
     <tests>
        <test>
            <param name="input_object" value="scPred_object.rds" />
            <param name="prediction_column" value="cell_type2" />
            <output name="output_obj_path" file="scPred_feat_space.rds" compare="sim_size" />
        </test>
    </tests>
    <help><![CDATA[
    @HELP@

5:17325882fa72

    <macros>
         <import>scpred_macros.xml</import>
    </macros>
    <expand macro='requirements' />
    <command detect_errors='exit_code'><![CDATA[
        scpred_get_feature_space.R  --input-object '${input_object}'  --prediction-column '${prediction_column}'   --output-path '${output_obj_path}' 
     
        #if $correction_method
        --correction-method '${correction_method}' 
        #end if
        #if $significance_threshold
        --significance-threshold '${significance_threshold}'
        #end if 
        #if $reduction_parameter
        --reduction-parameter '${reduction_parameter}'
        #end if 


        ]]></command>
    <inputs>
        <param type='data' name='input_object' label='Input Seurat object' format='rdata' help='Input Seurat object in .rds format' />
        <param type='text' name='prediction_column' optional="true" value="cell_type" label='Prediction Column' help='Name of the metadata column that contains training labels' />
        <param type='text' name='correction_method' label='Correction Method' optional='true' value="fdr" help='Method for mulpiple testing correction' />
        <param type='float' name='significance_threshold' label='Significance Threshold' optional='true' value="1.0" help='Significance threshold for principal components explaining class identity' />
        <param type='text' name='reduction_parameter' label='Reduction Parameter' optional='true' value="pca" help='Name of reduction in Seurat objet to be used to determine the feature space. Default: "pca"' />
        
    </inputs>
    <outputs>
        <data name='output_obj_path' format='rdata' />
    </outputs>
     <tests>
        <test>
            <param name="input_object" value="reference_pbmc.rds" />
            <output name="output_obj_path" file="scPred_feat_space.rds" compare="sim_size" />
        </test>
    </tests>
    <help><![CDATA[
    @HELP@