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#' Aggregate feature sets in a SummarizedExperiment
#'
#' Sum together expression values (by default, counts) for each feature set
#' in each cell of a \linkS4class{SummarizedExperiment} object.
#'
#' @param x A \linkS4class{SummarizedExperiment} containing an expression matrix.
#' @inheritParams sumCountsAcrossFeatures
#' @param ... Further arguments to be passed to \code{sumCountsAcrossFeatures}.
#' @param use.assay.type A character or integer vector specifying the assay(s) of \code{x} containing expression matrices.
#' @param use_exprs_values Soft-deprecated equivalent of \code{use.assay.type}.
#'
#' @return
#' A SummarizedExperiment of the same class as \code{x} is returned,
#' containing summed matrices generated by \code{sumCountsAcrossFeatures} on all assays in \code{use.assay.type}.
#'
#' If \code{ids} is a factor, row metadata is retained for the first instance of a feature from each set in \code{ids}.
#' This behavior assumes that \code{ids} specifies duplicates of the same gene, such that the first instance is a reasonable choice.
#'
#' If \code{ids} is a list, row metadata is simply discarded.
#' This behavior assumes that \code{ids} specifies gene sets such that any existing gene-level metadata is meaningless.
#'
#' @seealso
#' \code{\link{sumCountsAcrossFeatures}}, which does the heavy lifting.
#'
#' @author Aaron Lun
#'
#' @examples
#' example_sce <- mockSCE()
#' ids <- sample(LETTERS, nrow(example_sce), replace=TRUE)
#' aggr <- aggregateAcrossFeatures(example_sce, ids)
#' aggr
#'
#' @export
#' @importFrom SummarizedExperiment assays<- rowData rowData<- rowRanges<- assayNames
#' @importFrom GenomicRanges GRangesList GRanges
aggregateAcrossFeatures <- function(x, ids, ..., use.assay.type="counts", use_exprs_values=NULL) {
use.assay.type <- .replace(use.assay.type, use_exprs_values)
collected <- list()
for (i in seq_along(use.assay.type)) {
collected[[i]] <- sumCountsAcrossFeatures(x, ids=ids, ..., exprs_values=use.assay.type[i])
}
if (is.numeric(use.assay.type)) {
names(collected) <- assayNames(x)[use.assay.type]
} else {
names(collected) <- use.assay.type
}
if (is.list(ids)) {
x <- x[rep(1L, nrow(collected[[1]])),]
# Wiping out the row metadata.
if (is(x, "RangedSummarizedExperiment")) {
rowRanges(x) <- rep(GRangesList(GRanges()), nrow(x))
} else {
rowData(x) <- rowData(x)[,0]
}
} else {
x <- x[match(rownames(collected[[1]]), as.character(ids)),]
}
assays(x, withDimnames=FALSE) <- collected
rownames(x) <- rownames(collected[[1]])
x
}
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