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How to adjust FDR in plotMD?

Hi everyone.

Is it possible to adjust FDR in plotMD? There is no such function in the command description (https://www.rdocumentation.org/packages/limma/versions/3.28.14/topics/plotMD ), but it's quite necessary.

Thanks for any help!

rna-seq

1 answer

Hey Tanya,

There is no filtering occurring in limma::plotMD() with regard to p-values. The function produces a plot for log mean (x-axis) versus log ratio (y-axis).

However, there is functonality provided that permits you to colour shade certain points, e.g., those genes that pass, e.g., 5% FDR. Taking the example from the manual page:

require(limma)
A <- runif(1000,4,16)
y <- A + matrix(rnorm(1000*3,sd=0.2),1000,3)
status <- rep(c(0,-1,1),c(950,40,10))
y[,1] <- y[,1] + status
plotMD(y, column=1, status=status, values=c(-1,1), hl.col=c("blue","red"))

MA <- new("MAList")
MA$A <- runif(300,4,16)
MA$M <- rt(300,df=3)

# Spike-in values
MA$M[1:3] <- 0
MA$M[4:6] <- 3
MA$M[7:9] <- -3

status <- rep("Gene",300)
status[1:3] <- "M=0"
status[4:6] <- "M=3"
status[7:9] <- "M=-3"
values <- c("M=0","M=3","M=-3")
hl.col <- c("blue","red","green")

plotMD(MA,main="MA-Plot with 12 spiked-in points",
       status=status, values=values, hl.col=hl.col)

f

Take a closer look at the status, values, and hl.col variables, and then I am sure that you will figure it out.

Kevin

Are you using FPKM expression units?

No, it's just EdgeR results after Featurecounts.

Cool. You should check to see which genes have those extremely low fold changes and then try to understand if it is a genuine result or not. For example, check that they are not low-expressed genes, which can result in unrealistic fold-changes

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