Create volcano plot from log2FC and adjusted pvalues data frame — degVolcano • DEGreport

# Create volcano plot from log2FC and adjusted pvalues data frame

`degVolcano.Rd`

Create volcano plot from log2FC and adjusted pvalues data frame

    degVolcano(stats, side = "both",
      title = "Volcano Plot with Marginal Distributions",
      pval.cutoff = 0.05, lfc.cutoff = 1, shade.colour = "orange",
      shade.alpha = 0.25, point.colour = "gray", point.alpha = 0.75,
      point.outline.colour = "darkgray", line.colour = "gray",
      plot_text = NULL)

## Arguments

stats | data.frame with two columns: logFC and Adjusted.Pvalue
side | plot UP, DOWN or BOTH de-regulated points
title | title for the figure
pval.cutoff | cutoff for the adjusted pvalue. Default 0.05
lfc.cutoff | cutoff for the log2FC. Default 1
shade.colour | background color. Default orange.
shade.alpha | transparency value. Default 0.25
point.colour | colours for points. Default gray
point.alpha | transparency for points. Default 0.75
point.outline.colour | Default darkgray
line.colour | Defaul gray
plot_text | data.frame with three columns: logFC, Pvalue, Gene name

## Value

The function will plot volcano plot together with density of the fold change and p-values on the top and the right side of the volcano plot.

## Details

This function was mainly developed by @jnhutchinson.

## Examples

    library(DESeq2)
    dds <- makeExampleDESeqDataSet(betaSD = 1)
    dds <- DESeq(dds)#> estimating size factors#> estimating dispersions#> gene-wise dispersion estimates#> mean-dispersion relationship#> final dispersion estimates#> fitting model and testingstats <- results(dds)[,c("log2FoldChange", "padj")]
    stats[["name"]] <- row.names(stats)
    degVolcano(stats, plot_text = stats[1:10,])#> Warning: Removed 1 rows containing missing values (geom_text_repel).