# HG changeset patch # User ppericard # Date 1583769212 14400 # Node ID b0ab97ffc2a14e007e440213063a0fe3ab2c16fb # Parent 0a3c83f2197a624f915c4f4d2e515cf3046edf1e planemo upload for repository https://github.com/bilille/galaxy-mixomics-blocksplsda commit 0bf5c0745f406f2eca9c708a062c975b1f7ea386 diff -r 0a3c83f2197a -r b0ab97ffc2a1 circleCor.xml --- a/circleCor.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/circleCor.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,7 +1,7 @@ - + - - + plots a correlation circle for the datasets whose correlation circles can be superimposed. This correlation circle contains the selected variables of these datasets which are included in a rectangle and the response variables. + r-base r-ellipse @@ -10,7 +10,7 @@ - + @@ -32,16 +32,24 @@ - - - + + + - + @@ -50,10 +58,14 @@ - - - - + + + + diff -r 0a3c83f2197a -r b0ab97ffc2a1 circleCor_wrapper.R --- a/circleCor_wrapper.R Fri Oct 25 07:10:59 2019 -0400 +++ b/circleCor_wrapper.R Mon Mar 09 11:53:32 2020 -0400 @@ -76,8 +76,11 @@ print(blocks_vector) +# pdf(args$output_pdf, width=12, height=9) +pdf(args$output_pdf) -pdf(args$output_pdf, width=12, height=9) +mar = c(5.1, 4.1, 4.1, 9.1) +par(mar = mar) varSelect = circleCor(liste_dataframe_cor_comp_var_global = liste_dataframe_cor_comp_var_global, liste_vec_indice_blockSelect = liste_vec_indice_blockSelect, diff -r 0a3c83f2197a -r b0ab97ffc2a1 computeMatSimilarity.xml --- a/computeMatSimilarity.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/computeMatSimilarity.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,12 +1,12 @@ - + - - + performs the computation of the similarities. The similarity between two variables is an approximation of the correlation between these two variables. + r-argparse - + @@ -21,7 +21,9 @@ - + diff -r 0a3c83f2197a -r b0ab97ffc2a1 matCor_addVar.xml --- a/matCor_addVar.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/matCor_addVar.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,12 +1,12 @@ - + - - + computes all the correlations needed to plot a correlation circle and determines which correlation circles can be superimposed + bioconductor-mixomics r-argparse - + @@ -24,9 +24,15 @@ - - - + + + diff -r 0a3c83f2197a -r b0ab97ffc2a1 mixomics_blocksplsda.xml --- a/mixomics_blocksplsda.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/mixomics_blocksplsda.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,12 +1,12 @@ - + performs N-integration and feature selection with Projection to Latent Structures models (PLS) with sparse Discriminant Analysis - + bioconductor-mixomics r-argparse - + @@ -47,16 +47,31 @@ - - - + + + - - - - + + + +
- + + +
- + - + diff -r 0a3c83f2197a -r b0ab97ffc2a1 mixomics_blocksplsda_script.R --- a/mixomics_blocksplsda_script.R Fri Oct 25 07:10:59 2019 -0400 +++ b/mixomics_blocksplsda_script.R Mon Mar 09 11:53:32 2020 -0400 @@ -141,18 +141,18 @@ ################### mixomics_result <- block.splsda(X = list_X, - Y = Y, - ncomp = args$ncomp, - keepX = keepX, - design = design, - scheme = args$scheme, - mode = args$mode, - scale = args$scale, - init = args$init, - tol = args$tol, - max.iter = args$maxiter, - near.zero.var = args$nearzerovar, - all.outputs = TRUE) + Y = Y, + ncomp = args$ncomp, + keepX = keepX, + design = design, + scheme = args$scheme, + mode = args$mode, + scale = args$scale, + init = args$init, + tol = args$tol, + max.iter = args$maxiter, + near.zero.var = args$nearzerovar, + all.outputs = TRUE) print("Block.splsda object:") print(mixomics_result) diff -r 0a3c83f2197a -r b0ab97ffc2a1 mixomics_plotindiv.xml --- a/mixomics_plotindiv.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/mixomics_plotindiv.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,12 +1,12 @@ - + provides scatter plots for individuals (experimental units) representation in (sparse)(I)PCA,(regularized)CCA, (sparse)PLS(DA) and (sparse)(R)GCCA(DA) - + bioconductor-mixomics r-argparse - + @@ -23,10 +23,14 @@ - +
- - + +
diff -r 0a3c83f2197a -r b0ab97ffc2a1 mixomics_plotvar.xml --- a/mixomics_plotvar.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/mixomics_plotvar.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,12 +1,12 @@ - + provides variables representation for (regularized) CCA, (sparse) PLS regression, PCA and (sparse) Regularized generalised CCA - + bioconductor-mixomics r-argparse - + @@ -23,10 +23,15 @@ - +
- - + +
diff -r 0a3c83f2197a -r b0ab97ffc2a1 networkVar.xml --- a/networkVar.xml Fri Oct 25 07:10:59 2019 -0400 +++ b/networkVar.xml Mon Mar 09 11:53:32 2020 -0400 @@ -1,13 +1,13 @@ - + - - + creates a network between selected variables of datasets and the response variables. In the network, the similarity between two variables is associated with the link between these two variables. + bioconductor-mixomics r-igraph r-argparse - + @@ -23,7 +23,7 @@ #if str($var_of_interest_file) !='': --interest_var_file ${var_of_interest_file} #end if - + --responses_var ${select_responses_var} --output_graph ${output_graph} @@ -31,15 +31,26 @@ - - - - + + + + - + - - + +