Mercurial > repos > ppericard > viscorvar
diff mixomics_plotvar.xml @ 4:d4e9f7546dfa draft
"planemo upload for repository https://gitlab.com/bilille/galaxy-viscorvar commit 579dc54316e8ede493f86f434a87d3d7b692b023"
author | ppericard |
---|---|
date | Tue, 17 Nov 2020 13:01:44 +0000 |
parents | c8533e9298e5 |
children | 88c1fd2ac110 |
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--- a/mixomics_plotvar.xml Fri Oct 23 11:26:18 2020 +0000 +++ b/mixomics_plotvar.xml Tue Nov 17 13:01:44 2020 +0000 @@ -1,4 +1,4 @@ -<tool id="mixomics_plotvar" name="mixOmics plotVar" version="@TOOL_VERSION@+galaxy1" profile="16.04" workflow_compatible="true"> +<tool id="mixomics_plotvar" name="mixOmics plotVar" version="@TOOL_VERSION@+galaxy2" profile="16.04" workflow_compatible="true"> <description>provides variables representation for (regularized) CCA, (sparse) PLS regression, PCA and (sparse) Regularized generalised CCA</description> @@ -21,20 +21,18 @@ --output_pdf $output_pdf - @COMMAND_LOG_EXIT@ - ]]></command> <inputs> <param name="input_rdata" type="data" format="rdata" label="Input RData file from (sparse)(I)PCA, (regularized)CCA, (sparse)PLS(DA) or (sparse)(R)GCCA(DA)" - help="This is the RData output file from the block.splsda function." /> + help="this is the RData output file from the block.splsda function" /> <section name="adv" title="Advanced Options" expanded="false"> <param name="legend" type="boolean" checked="true" truevalue="--legend" falsevalue="" label="Plot legend" /> <param name="cutoff" type="float" value="0" min="0" max="1" label="Cut-off" - help="Only selected variables whose correlation with the first or second axis is greater than Cut-off in absolute value will be plotted." /> + help="only selected variables whose correlation with the first or second axis is greater than Cut-off in absolute value will be plotted" /> </section> </inputs> @@ -61,8 +59,8 @@ Description ----------- -The plotVar function is part of the mixOmics package for exploration and integration of Omics datasets. -Provides variables representation for (regularized) CCA, (sparse) PLS regression, PCA and (sparse) Regularized generalised CCA. +This tool allows visualizing the variables of a omics dataset which are correlated with the variables +of the other omic datasets and the response variable in a correlation circle. ----------------- Workflow position