Mercurial > repos > ebi-gxa > scpred_train_model
changeset 7:a7269f8f45aa draft default tip
"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 | b3c543769af9 |
children | |
files | scpred_macros.xml scpred_train_model.xml |
diffstat | 2 files changed, 24 insertions(+), 5 deletions(-) [+] |
line wrap: on
line diff
--- a/scpred_macros.xml Fri Aug 14 11:06:23 2020 -0400 +++ b/scpred_macros.xml Fri Nov 27 13:46:23 2020 +0000 @@ -1,10 +1,10 @@ <macros> - <token name="@TOOL_VERSION@">1.0.1</token> + <token name="@TOOL_VERSION@">1.0.2</token> <token name="@HELP@">More information can be found at https://joseah.github.io/post/introduction-to-scpred/</token> <token name="@PROFILE@">18.01</token> <xml name="requirements"> <requirements> - <requirement type="package" version="0.0.9">scpred-cli</requirement> + <requirement type="package" version="0.1.0">scpred-cli</requirement> <yield/> </requirements> </xml> @@ -15,6 +15,7 @@ </xml> <token name="@VERSION_HISTORY@"><![CDATA[ **Version history** + 1.0.2+galaxy0: Update to a new version of r-scpred 1.0.1+galaxy0: Update output format from csv to tsv 1.0.0+galaxy0: Initilal contribution. Andrey Solovyev, Expression Atlas team https://www.ebi.ac.uk/gxa/home at EMBL-EBI https://www.ebi.ac.uk/. ]]></token>
--- a/scpred_train_model.xml Fri Aug 14 11:06:23 2020 -0400 +++ b/scpred_train_model.xml Fri Nov 27 13:46:23 2020 +0000 @@ -5,24 +5,42 @@ </macros> <expand macro="requirements" /> <command detect_errors="exit_code"><![CDATA[ - scpred_train_model.R --input-object "${input_object}" --model "${model}" --output-path "${output_obj_path}" --train-probs-plot "${train_probs_plot}" + 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}" + #if $train_id --train-id '${train_id}' #end if + #if $resample_method + --resample-method '${resample_method}' + #end if + #if $reclassify + --reclassify "${reclassify}" + #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="train_id" optional="true" label="Dataset ID" help="ID of the training dataset" /> <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" /> + <param type="text" name="resample_method" optional="true" value="cv" label="Resample Method" help="Resampling method used for model fit evaluation" /> + <param type="integer" name="iter_num" optional="true" value="5" label="Number of Iterations" help="Number of resampling iterations. Default: 5" /> + <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" /> + <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" /> + <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'." /> + <param type="boolean" checked="false" name="return_data" label="Return Data" help="If TRUE, training data is returned within scPred object. Default: False"/> + <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'." /> + <param type="text" name="reclassify" optional="true" label="Cells to Reclassify" help="Cell types to reclassify using a different model" /> + </inputs> <outputs> <data name="output_obj_path" format="rdata" /> - <data name="train_probs_plot" format="png" /> </outputs> <tests> <test> <param name="input_object" value="scPred_feat_space.rds" /> - <output name="output_obj_path" file="scPred_trained.rds" compare="sim_size" /> + <param name="train_id" value="E-ENAD-16" /> + <output name="output_obj_path" file="scPred_trained.rds" compare="sim_size" delta="10000000"/> </test> </tests> <help><![CDATA[