@@ -1,6 +1,8 @@

 selectMulti <- function(measurementsTrain, classesTrain, params, verbose = 0)

           {

-              assayTrain <- sapply(unique(S4Vectors::mcols(measurementsTrain)[["assay"]]), function(assay) measurementsTrain[, S4Vectors::mcols(measurementsTrain)[["assay"]] %in% assay], simplify = FALSE)

+              assaysIndices <- lapply(unique(S4Vectors::mcols(measurementsTrain)[["assay"]]), function(assay) which(S4Vectors::mcols(measurementsTrain)[["assay"]] == assay))

+              assayTrain <- lapply(assaysIndices, function(assayIndices) measurementsTrain[, assayIndices])

+              

               featuresIndices <- mapply(.doSelection, 

                                          measurements = assayTrain,

                                          modellingParams = params,

@@ -8,7 +10,8 @@ selectMulti <- function(measurementsTrain, classesTrain, params, verbose = 0)

                                                          crossValParams = CrossValParams(permutations = 1, folds = 5), ###### Where to get this from?

                                                          verbose = 0), SIMPLIFY = FALSE

                                         )

-              

-              unique(unlist(lapply(featuresIndices, "[[", 2)))

+

+              unlist(mapply(function(allDataIndices, withinIndices) allDataIndices[withinIndices],

+                     assaysIndices, lapply(featuresIndices, "[[", 2), SIMPLIFY = FALSE))

 }

 attr(selectMulti, "name") <- "Union Selection"

@@ -131,8 +131,8 @@

         paramList <- append(paramList, tuneCombo)

       do.call(featureRanking, paramList)

     })

-    

-    if(attr(featureRanking, "name") == "previousSelection") # Actually selection not ranking.

+

+    if(attr(featureRanking, "name") %in% c("previousSelection", "Union Selection")) # Actually selection not ranking.

       return(list(NULL, rankings[[1]], NULL))

     if(crossValParams@tuneMode == "none") # No parameters to choose between.