This function pot the p-valyes distribution colored by the quantiles of the standard desviation of count data.

degVar(pvalues, counts)



pvalues of DEG analysis


Matrix with counts for each samples and each gene. row number should be the same length than pvalues vector.


ggplot2 object


data(humanGender) library(DESeq2) idx <- c(1:10, 75:85) dds <- DESeqDataSetFromMatrix(assays(humanGender)[[1]][1:1000, idx], colData(humanGender)[idx,], design=~group) dds <- DESeq(dds)
#> using pre-existing size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing
#> -- replacing outliers and refitting for 1 genes #> -- DESeq argument 'minReplicatesForReplace' = 7 #> -- original counts are preserved in counts(dds)
#> estimating dispersions
#> fitting model and testing
res <- results(dds) degVar(res[, 4], counts(dds))