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##' Extension for the edgeR package
##'
##' This method extends the edgeR package by offering the functionality to plot
##' the effect of the normalization factor.
##'
##'
##' @aliases plotNormalizationFactors
##' plotNormalizationFactors,DGEList,character,character-method
##' @name edgeR additional methods
##' @rdname edgeR-methods
##' @param obj An object of class \code{\linkS4class{DGEList}}
##' @param cond1 A character string describing the first condition
##' @param cond2 A character string describing the second condition
##' @return none
##' @author Nicolas Delhomme
##' @keywords methods
##' @examples
##'
##' \dontrun{
##' ## create the object
##' dgeList <- DGEList(counts,group)
##' ## calculate the sie factors
##' dgeList <- calcNormFactors(dgeList)
##' ## plot them
##' apply(combn(rownames(dgeList$samples),2),
##' 2,
##' function(co,obj){plotNormalizationFactors(obj,co[1],co[2])},dgeList)
##' }
##'
## This code was extracted from the edgeR vignette
## Robinson et al.
setMethod(
f="plotNormalizationFactors",
signature=c("DGEList","character","character"),
definition=function(obj=DGEList(),cond1=character(1),cond2=character(1)){
## check that the cond are in the samples
if(nrow(obj$samples)==0){
stop("Your 'DGEList' does not contain sample information!")
}
if(is.null(rownames(obj$samples))){
stop("Your 'DGEList' samples data.frame has no row names!!")
}
if(!(all(c(cond1,cond2) %in% rownames(obj$samples)))){
stop("The provided conditions do not exist in your 'DGEList' samples data.frame. Check the row names.")
}
## raw data
maPlot(obj$counts[, cond1], obj$counts[, cond2],
normalize = TRUE, pch = 19,
cex = 0.4, ylim = c(-8, 8),
main=paste("Smear plot",
rownames(obj$samples[cond1,]),
paste("(",obj$samples[cond1,"group"],")",sep=""),
"vs.\n",
rownames(obj$samples[cond2,]),
paste("(",obj$samples[cond2,"group"],")",sep=""),
"before normalization"))
grid(col = "blue")
abline(h = log2(obj$samples$norm.factors[match(cond1,rownames(obj$samples))]/obj$samples$norm.factors[match(cond2,rownames(obj$samples))]),
col = "red", lwd = 4)
eff.libsize <- obj$samples$lib.size * obj$samples$norm.factors
names(eff.libsize) <- rownames(obj$samples)
## norm data
maPlot(obj$counts[, cond1]/eff.libsize[cond1], obj$counts[, cond2]/eff.libsize[cond2],
normalize = FALSE, pch = 19, cex = 0.4, ylim = c(-8, 8),
main=paste("Smear plot",
rownames(obj$samples[cond1,]),
paste("(",obj$samples[cond1,"group"],")",sep=""),
"vs.\n",
rownames(obj$samples[cond2,]),
paste("(",obj$samples[cond2,"group"],")",sep=""),
"after normalization"))
grid(col = "blue")
})
setMethod(
f="plotDispersionEstimates",
signature=c("DGEList"),
definition=function(obj=DGEList()){
.Defunct(new="plotBCV",msg="This method is defunct due to change in
the edgeR DGEList object.")
})
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