#' Plot Dispersion Estimates - nicer ggplot version of DESeq graph
#'
#' @param cds CountDataSet, required
#' @return plot
#' @seealso \code{\link{DESeq}} for description of the Dispersion plots
#' @export
#' @examples
#' ggplotDispEsts(cds)
ggplotDispEsts = function(cds) {
estimates = data.frame(means = rowMeans(counts(cds, normalized=TRUE)),
variance = fitInfo(cds)$perGeneDispEsts)
xg = 10^seq(-0.5, 5, length.out=300)
yg = fitInfo(cds)$dispFun(xg)
fitline = data.frame(xg=xg, yg=yg)
p = ggplot(estimates, aes(means, variance)) + geom_point(size=1, alpha=0.4) +
scale_x_log10() + scale_y_log10() +
geom_line(data=fitline, aes(xg, yg), color="red") +
labs(title="Dispersion estimation while pooling all samples") +
xlab("mean number of mapped reads per gene") +
ylab("estimated dispersion")
p
}
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