Hi everyone,

I am trying to plot Volcano plots for analysis mostly from Limma. I found 2 sources- one that labels points above certain thresholds of adjusted p values and logFC values and another one that uses the MarrayLM object as input and labels the top gene hits.

Here are the source links:

1)  http://www.gettinggeneticsdone.com/2014/05/r-volcano-plots-to-visualize-rnaseq-microarray.html

2) http://web.mit.edu/~r/current/arch/i386_linux26/lib/R/library/limma/html/volcanoplot.html (can only be used for Limma I believe)

Is there a way I can label the top 20 most up-regulated genes and 20 most down-regulated genes as per LogFC values and also change the color of the points that represent them? Is it possible to only highlight points that meet certain conditions in different colors and to label them (as in Source 1) or to label the top gene hits only (as in Source 2)? 

Thanks for all the help.

Hi,

Not sure exactly what you mean, but looking at the first example you can identify the threshold for fold change and then almost unaltered use Turners example.

threshold.high <- sort(res$log2FoldChange, decreasing = TRUE)[20]
threshold.low <- sort(res$log2FoldChange, decreasing = FALSE)[20]
with(res, plot(log2FoldChange, -log10(pvalue), pch=20,
     main="Volcano plot", xlim=c(-2.5,2)))
with(subset(res, log2FoldChange > threshold.high),
     points(log2FoldChange, -log10(pvalue), pch=20, col="red"))
with(subset(res, log2FoldChange < threshold.low),
     points(log2FoldChange, -log10(pvalue), pch=20, col="red"))
with(subset(res, log2FoldChange > threshold.high),
     textxy(log2FoldChange, -log10(pvalue), labs=Gene, cex=.8))
with(subset(res, log2FoldChange < threshold.low),
     textxy(log2FoldChange, -log10(pvalue), labs=Gene, cex=.8))