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#' Compute log-normalized expression values
#'
#' Compute log-transformed normalized expression values from a count matrix in a \linkS4class{SingleCellExperiment} object.
#'
#' @param x A \linkS4class{SingleCellExperiment} or \linkS4class{SummarizedExperiment} object containing a count matrix.
#' @inheritParams normalizeCounts
#' @param use.altexps Logical scalar indicating whether normalization should be performed for alternative experiments in \code{x}.
#'
#' Alternatively, a character vector specifying the names of the alternative experiments to be normalized.
#'
#' Alternatively \code{NULL}, in which case no calculations are performed on the alternative experiments.
#' @param ... For the generic, additional arguments passed to specific methods.
#'
#' For the methods, additional arguments passed to \code{\link{normalizeCounts}}.
#' @param name String containing an assay name for storing the output normalized values.
#' Defaults to \code{"logcounts"} when \code{log=TRUE} and \code{"normcounts"} otherwise.
#' @param BPPARAM A \linkS4class{BiocParallelParam} object specifying how library size factor calculations should be parallelized.
#' Only used if \code{size.factors} is not specified.
#' @param use_altexps Soft-deprecated equivalent to the argument above.
#'
#' @details
#' This function is a convenience wrapper around \code{\link{normalizeCounts}}.
#' It returns a \linkS4class{SingleCellExperiment} or \linkS4class{SummarizedExperiment} containing the normalized values in a separate assay.
#' This makes it easier to perform normalization by avoiding book-keeping errors during a long analysis workflow.
#'
#' If \code{x} is a \linkS4class{SingleCellExperiment} that contains alternative Experiments, normalized values can be computed and stored within each alternative experiment by setting \code{use.altexps} appropriately.
#' By default, \code{use.altexps=FALSE} to avoid problems from attempting to library size-normalize alternative experiments that have zero total counts for some cells.
#'
#' If \code{size.factors=NULL}, size factors are obtained following the rules in \code{\link{normalizeCounts}}.
#' This is done independently for the main and alternative Experiments when \code{use.altexps} is specified,
#' i.e. no information is shared between Experiments by default.
#' However, if \code{size.factors} is supplied, it will override any size factors available in any Experiment.
#'
#' @return
#' \code{x} is returned containing the (log-)normalized expression values in an additional assay named as \code{name}.
#'
#' If \code{x} is a \linkS4class{SingleCellExperiment}, the size factors used for normalization are stored in \code{\link{sizeFactors}}.
#' These are centered if \code{center.size.factors=TRUE}.
#'
#' If \code{x} contains alternative experiments and \code{use.altexps=TRUE}, each of the alternative experiments in \code{x} will also contain an additional assay.
#' This can be limited to particular \code{\link{altExps}} entries by specifying them in \code{use.altexps}.
#'
#' @author Aaron Lun, based on code by Davis McCarthy
#' @seealso
#' \code{\link{normalizeCounts}}, which is used to compute the normalized expression values.
#'
#' @examples
#' example_sce <- mockSCE()
#'
#' # Standard library size normalization:
#' example_sce2 <- logNormCounts(example_sce)
#' assayNames(example_sce2)
#' logcounts(example_sce2)[1:5,1:5]
#'
#' # Without logging, the assay is 'normcounts':
#' example_sce2 <- logNormCounts(example_sce, log=FALSE)
#' assayNames(example_sce2)
#' normcounts(example_sce2)[1:5,1:5]
#'
#' # Pre-loading with size factors:
#' example_sce2 <- computeMedianFactors(example_sce)
#' example_sce2 <- logNormCounts(example_sce2)
#' logcounts(example_sce2)[1:5,1:5]
#'
#' # Also normalizing the alternative experiments:
#' example_sce2 <- logNormCounts(example_sce, use.altexps="Spikes")
#' logcounts(altExp(example_sce2))[1:5,1:5]
#'
#' @name logNormCounts
NULL
#' @export
#' @rdname logNormCounts
setGeneric("logNormCounts", function(x, ...) standardGeneric("logNormCounts"))
#' @export
#' @rdname logNormCounts
#' @importClassesFrom SummarizedExperiment SummarizedExperiment
setMethod("logNormCounts", "SummarizedExperiment", function(x, size.factors=NULL, log=TRUE,
pseudo.count=1, center.size.factors=TRUE, ..., assay.type="counts", name=NULL, BPPARAM=SerialParam(),
size_factors=NULL, pseudo_count=NULL, center_size_factors=NULL, exprs_values=NULL)
{
size.factors <- .replace(size.factors, size_factors)
pseudo.count <- .replace(pseudo.count, pseudo_count)
center.size.factors <- .replace(center.size.factors, center_size_factors)
assay.type <- .replace(assay.type, exprs_values)
FUN <- .se_lnc(assay.type=assay.type, log=log, pseudo.count=pseudo.count, ..., name=name, BPPARAM=BPPARAM)
FUN(x, size.factors=size.factors, center.size.factors=center.size.factors)
})
#' @importFrom SummarizedExperiment assay<-
.se_lnc <- function(assay.type, log, pseudo.count, ..., name) {
args <- list(..., assay.type=assay.type, log=log, pseudo.count=pseudo.count)
if (is.null(name)) {
name <- if (log) "logcounts" else "normcounts"
}
function(x, ...) {
out <- do.call(normalizeCounts, c(list(x, ...), args))
assay(x, name) <- out
x
}
}
#' @export
#' @rdname logNormCounts
#' @importFrom BiocGenerics sizeFactors sizeFactors<-
#' @importFrom SingleCellExperiment altExp altExp<- int_metadata int_metadata<-
#' @importClassesFrom SingleCellExperiment SingleCellExperiment
setMethod("logNormCounts", "SingleCellExperiment", function(x, size.factors=NULL, log=TRUE, pseudo.count=1,
center.size.factors=TRUE, ..., assay.type="counts", use.altexps=FALSE, name=NULL, BPPARAM=SerialParam(),
size_factors=NULL, pseudo_count=NULL, center_size_factors=NULL, exprs_values=NULL, use_altexps=NULL)
{
size.factors <- .replace(size.factors, size_factors)
pseudo.count <- .replace(pseudo.count, pseudo_count)
center.size.factors <- .replace(center.size.factors, center_size_factors)
use.altexps <- .replace(use.altexps, use_altexps)
assay.type <- .replace(assay.type, exprs_values)
# Guarantee that we get (centered) size factors back out.
original <- size.factors
if (is.null(size.factors)) {
size.factors <- sizeFactors(x)
if (is.null(size.factors)) {
size.factors <- librarySizeFactors(x, assay.type=assay.type, BPPARAM=BPPARAM)
}
}
size.factors <- .center.size.factors(size.factors, center.size.factors)
sizeFactors(x) <- size.factors
# Set center.size.factors=FALSE, as we've already centered above.
FUN <- .se_lnc(assay.type=assay.type, log=log, pseudo.count=pseudo.count, ..., name=name)
x <- FUN(x, size.factors=size.factors, center.size.factors=FALSE)
if (log) {
if (is.null(int_metadata(x)$scater)) {
int_metadata(x)$scater <- list()
}
int_metadata(x)$scater$pseudo.count <- pseudo.count
}
use.altexps <- .use_names_to_integer_indices(use.altexps, x=x, nameFUN=altExpNames, msg="use.altexps")
for (i in use.altexps) {
tryCatch({
altExp(x, i) <- FUN(altExp(x, i), size.factors=original, center.size.factors=center.size.factors)
}, error=function(err) {
stop(paste0(sprintf("failed to normalize 'altExp(x, %s)'\n", deparse(i)), conditionMessage(err)))
})
}
x
})
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