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add weights in pseudbulkDGE for edgeR analysis #107

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add weights in pseudbulkDGE for edgeR analysis #107

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9770552
add weights in pseudbulkDGE for edgeR analysis
koenvandenberge Jan 31, 2023
89f7755
subset weights and add docs
koenvandenberge Feb 2, 2023
603b671
fix typo
koenvandenberge Feb 2, 2023
c325d39
subset weights based on gene filtering
koenvandenberge Feb 3, 2023
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25 changes: 19 additions & 6 deletions R/pseudoBulkDGE.R
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,8 @@
#' @param row.data A \linkS4class{DataFrame} containing additional row metadata for each gene in \code{x},
#' to be included in each of the output DataFrames.
#' This should have the same number and order of rows as \code{x}.
#' @param weights A vector or matrix of weights. If vector, it is assumed the weights are equal for all genes. Alternatively,
#' a matrix with the same dimensions as \code{x} can be provided.
#' @param ... For the generic, additional arguments to pass to individual methods.
#'
#' For the SummarizedExperiment method, additional arguments to pass to the ANY method.
Expand Down Expand Up @@ -143,7 +145,7 @@ NULL

.pseudo_bulk_master <- function(x, col.data, label, design, coef, contrast=NULL,
condition=NULL, lfc=0, include.intermediates=TRUE, row.data=NULL, sorted=FALSE,
method=c("edgeR", "voom"), qualities=TRUE, robust=TRUE, sample=NULL)
method=c("edgeR", "voom"), qualities=TRUE, robust=TRUE, sample=NULL, weights=NULL)
{
if (!is.null(sample)) {
.Deprecated(msg="'sample=' is deprecated and will be ignored")
Expand All @@ -154,14 +156,14 @@ NULL
.pseudo_bulk_dge(x=x, col.data=col.data, label=label, condition=condition,
design=design, coef=coef, contrast=contrast, lfc=lfc, row.data=row.data,
sorted=sorted, include.intermediates=include.intermediates,
method=match.arg(method), qualities=qualities, robust=robust)
method=match.arg(method), qualities=qualities, robust=robust, weights=weights)
}

#' @importFrom edgeR DGEList
#' @importFrom S4Vectors DataFrame SimpleList metadata metadata<-
.pseudo_bulk_dge <- function(x, col.data, label, design, coef, contrast=NULL,
condition=NULL, lfc=0, null.lfc.list=NULL, row.data=NULL, sorted=FALSE, include.intermediates=FALSE,
method=c("edgeR", "voom"), qualities=TRUE, robust=TRUE)
method=c("edgeR", "voom"), qualities=TRUE, robust=TRUE, weights=NULL)
{
de.results <- list()
failed <- character(0)
Expand All @@ -172,6 +174,14 @@ NULL
if (!is.null(contrast)) {
coef <- NULL
}

# Checks on weights
if(is.vector(weights)){
stopifnot(length(weights)==nrow(design))
weights <- matrix(weights,nrow=nrow(x), ncol=ncol(x), byrow=TRUE)
} else if(is.matrix(weights)){
stopifnot(all.equal(dim(weights),dim(x)))
}

for (i in sort(unique(label))) {
chosen <- i==label
Expand All @@ -180,6 +190,7 @@ NULL
curdata <- col.data[chosen,,drop=FALSE]
y <- DGEList(curx, samples=as.data.frame(curdata))
curcond <- condition[chosen]
curweights <- weights[,chosen]

curdesign <- try({
if (is.function(design)) {
Expand All @@ -196,7 +207,7 @@ NULL
} else {
args <- list(y, row.names=rownames(x), curdesign=curdesign, curcond=curcond,
coef=coef, contrast=contrast, lfc=lfc, null.lfc=null.lfc.list[[i]],
robust=robust, include.intermediates=include.intermediates)
robust=robust, include.intermediates=include.intermediates, weights=curweights)

if (method=="edgeR") {
stuff <- do.call(.pseudo_bulk_edgeR, args)
Expand Down Expand Up @@ -233,13 +244,15 @@ NULL
#' calcNormFactors filterByExpr topTags glmLRT glmFit glmTreat
#' @importFrom limma makeContrasts
.pseudo_bulk_edgeR <- function(y, row.names, curdesign, curcond, coef, contrast,
lfc, null.lfc, include.intermediates, robust=TRUE)
lfc, null.lfc, include.intermediates, robust=TRUE, weights=NULL)
{
ngenes <- nrow(y)
gkeep <- filterByExpr(y, design=curdesign, group=curcond)
y <- y[gkeep,]
y <- calcNormFactors(y)

if(!is.null(weights)) y$weights <- weights[gkeep,]

rank <- qr(curdesign)$rank
if (rank == nrow(curdesign) || rank < ncol(curdesign)) {
return(NULL)
Expand Down Expand Up @@ -301,7 +314,7 @@ NULL
#' @importFrom limma voom voomWithQualityWeights lmFit
#' contrasts.fit eBayes treat topTable makeContrasts
.pseudo_bulk_voom <- function(y, row.names, curdesign, curcond, coef, contrast,
lfc, null.lfc, include.intermediates, qualities=TRUE, robust=TRUE)
lfc, null.lfc, include.intermediates, qualities=TRUE, robust=TRUE, weights=NULL)
{
ngenes <- nrow(y)
gkeep <- filterByExpr(y, design=curdesign, group=curcond)
Expand Down