.filterFeatures <- function(expr, method) {
 
   ## filter out genes with constant expression values

   ## DelayedMatrixStats::rowSds() works for both base and 
   ## DelayedArray matrices

   sdGenes <- DelayedMatrixStats::rowSds(expr)

   ## the following fixes this bug, see issues
   ## https://github.com/rcastelo/GSVA/issues/54
   ## https://github.com/HenrikBengtsson/matrixStats/issues/204
   sdGenes[sdGenes < 1e-10] <- 0

   if (any(sdGenes == 0) || any(is.na(sdGenes))) {
     warning(sum(sdGenes == 0 | is.na(sdGenes)),
             " genes with constant expression values throuhgout the samples.")
     if (method != "ssgsea") {
       warning("Since argument method!=\"ssgsea\", genes with constant expression values are discarded.")
       expr <- expr[sdGenes > 0 & !is.na(sdGenes), ]
     }
   } 
 

   if (nrow(expr) < 2)
     stop("Less than two genes in the input assay object\n")
   
   if(is.null(rownames(expr)))
     stop("The input assay object doesn't have rownames\n")
   

   expr
 }

 ## maps gene sets content in 'gsets' to 'features', where 'gsets'
 ## is a 'list' object with character string vectors as elements,
 ## and 'features' is a character string vector object. it assumes
 ## features in both input objects follow the same nomenclature,
 .mapGeneSetsToFeatures <- function(gsets, features) {
 

   ## Aaron Lun's suggestion at
   ## https://github.com/rcastelo/GSVA/issues/39#issuecomment-765549620
   gsets2 <- CharacterList(gsets)
   mt <- match(gsets2, features)
   mapdgenesets <- as.list(mt[!is.na(mt)])

 
   if (length(unlist(mapdgenesets, use.names=FALSE)) == 0)
     stop("No identifiers in the gene sets could be matched to the identifiers in the expression data.")
 
   mapdgenesets
 }
 

 ## transforms a dgCMatrix into a list of its
 ## non-zero values by MARGIN (1 for row, 2 for column)
 .sparseToList <-function(dgCMat, MARGIN){
   MARGIN <- as.integer(MARGIN)
   J <- rep(1:ncol(dgCMat), diff(dgCMat@p))
   I <- dgCMat@i + 1
   x <- dgCMat@x
   if (MARGIN == 1L) {
     result <- split(x, I)
     names(result) <- rownames(dgCMat)[as.numeric(names(result))]
   } else if (MARGIN == 2L) {
     result <- split(x, J)
     names(result) <- colnames(dgCMat)[as.numeric(names(result))]
   }
   else {
     warning("invalid MARGIN; return NULL")
     result <- NULL
   }
   result
 }
 

 .dgCapply<-function(m,f, MARGIN){
   x <- lapply(.sparseToList(m, MARGIN), f)
   m@x <- unlist(x, use.names=FALSE)
   m
 }