#' @title test_diffs Statistics function to summarize expression
#' data of an se object, using ratios between selected treatments.
#' @description generateStats is a summary function used on various
#' expression data, using ratios between selected treatments.
#' @usage test_diffs(se, groupings= NULL, treatment1=NULL, treatment2=NULL,
#' mode_mean=TRUE, LOG2=TRUE)
#' @param se An se object.
#' @param groupings A grouping (annotation column); groupings="annotation.ZA".
#' @param treatment1 Symbol, treatment 1.
#' @param treatment2 Symbol, treatment 2.
#' @param mode_mean Boolean, Calculate RowMeans or RowMedians.
#' @param LOG2 Boolean, Calculate LOG2.
#' @details This function completes summary statistics of the expression of
#' the supplied se object.
#' @examples
#' data(hmel.se)
#' test_diffs(se, groupings='annotation.ZA',treatment1="Male",
#' treatment2="Female" )
#' @return Returns an invisible list of summary statistics,
#' kruskal test and raw data of an se object, using ratios
#' between selected treatments.
#' @author AJ Vaestermark, JR Walters.
#' @references The "doseR" package, 2018 (in press).
test_diffs <- function (se, groupings= NULL, treatment1=NULL,
treatment2=NULL, mode_mean=TRUE, LOG2=TRUE) {
if(is.null(groupings)) {
stop ('No groupings, e.g. groupings="something"...')
return (NULL)
}
if(length(assays(se)$rpkm) == 0) {
stop ('No RPKM data saved in count data object... cancelling...')
return (NULL)
}
if(is.null(treatment1) | is.null(treatment2) ) {
stop ('Indicate treatments, such as treatment1="A", treatment2="B"')
return (NULL)
}
MyGroups<-rowData(se)[[groupings]]
RM<- (
if(mode_mean) rowMeans(assays(se)$rpkm[,colData(se)$Treatment==treatment1]) else
matrixStats::rowMedians(assays(se)$rpkm[,colData(se)$Treatment==treatment1])
) / (
if(mode_mean) rowMeans(assays(se)$rpkm[,colData(se)$Treatment==treatment2]) else
matrixStats::rowMedians(assays(se)$rpkm[,colData(se)$Treatment==treatment2])
)
if(LOG2) { RM<-log2(RM) }
RM[is.infinite(RM)]<-NA
outsize <- 6
if(length(RM[is.na(RM)])>0) { outsize<-7 }
tmp <- split(RM, MyGroups)
val.summary <- vapply(tmp, summary, double(outsize) )
val.k <- kruskal.test(tmp)
names(tmp) <- levels(as.factor(MyGroups))
message("View output: outlist$kruskal, outlist$summary")
invisible( list("summary" = val.summary, "kruskal" = val.k, "data" = tmp) )
}# test_diffs
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