degQC {DEGreport} | R Documentation

## Plot main figures showing p-values distribution and mean-variance correlation

### Description

This function joins the output of `degMean`, `degVar` and `degMV` in a single plot. See these functions for further information.

### Usage

    degQC(counts, groups, object = NULL, pvalue = NULL)

### Arguments

`counts` | Matrix with counts for each samples and each gene.
`groups` | Character vector with group name for each sample in the same order than counts column names.
`object` | DEGSet oobject.
`pvalue` | pvalues of DEG analysis.

### Value

ggplot2 object

### Examples

    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)
    res <- results(dds)
    degQC(counts(dds, normalized=TRUE), colData(dds)[["group"]],
      pvalue = res[["pvalue"]])

[Package DEGreport version 1.16.0 Index]