Import from limma-trend approach

[lgeistlinger]

Alright here is an update for you @lgeistlinger.

I've been using import and I have a few suggestions. For importing limma data I think there needs to be a way for using data from the limma-trend approach. Check page 72 on the limma user guide.

Instead of using voom:

EnrichmentBrowser/R/import.R

Lines 120 to 132 in 4357b80

	#' # (3) import from voom/limma (RNA-seq count data)
	#' # (3a) create the expression data object
	#' library(limma)
	#' keep <- filterByExpr(counts, rdesign)
	#' el <- voom(counts[keep,], rdesign)
	#'
	#' # (3b) obtain differential expression results
	#' fit <- lmFit(el, rdesign)
	#' fit <- eBayes(fit, robust = TRUE)
	#' res <- topTable(fit, coef = 2, number = nrow(counts), sort.by = "none")
	#'
	#' # (3c) import
	#' se <- import(el, res)

You would use the limma-trend method:

#'   # (5) import from trend/limma (RNA-seq count data)
#'   # (5a) create the expression data object
#'   library(limma)
#'   keep <- filterByExpr(counts, rdesign)
#'   
> logCPM <- edgeR::cpm(counts[keep,], log=TRUE, prior.count=3)
#'   # (5b) obtain differential expression results 
> fit <- lmFit(logCPM, design)
> fit <- eBayes(fit, trend=TRUE)
> res <- topTable(fit, coef=ncol(design))

#'
#'   # (5c) import???
#'   se <- import(el, res)

Originally posted by @grabearummc in #23 (comment)

[lgeistlinger]

Thanks @grabearummc ! I'll be following up on that.

[lgeistlinger]

That is now possible (f884102).

EnrichmentBrowser/R/import.R

Line 150 in f884102

#' # (4) import from limma-trend (RNA-seq count data)

Thanks for pointing that out!