Forest plots using R and ggplot2

Abhijit over at Stat Bandit posted some nice code for making forest plots using ggplot2 in R. You see these lots of times in meta-analyses, or as seen in the BioVU demonstration paper. The idea is simple - on the x-axis you have the odds ratio (or whatever stat you want to show), and each line is a different study, gene, SNP, phenotype, etc. You draw a dot for the odds ratio point estimate, and lines extending from that point showing the confidence limits for that odds ratio.

Here's the R code, slightly modified from Abhijit's version:

	# d is a data frame with 4 columns
	# d$x gives variable names
	# d$y gives center point
	# d$ylo gives lower limits
	# d$yhi gives upper limits
	forestplot <- function(d, xlab="Odds Ratio", ylab="Study"){
	require(ggplot2)
	p <- ggplot(d, aes(x=x, y=y, ymin=ylo, ymax=yhi)) +
	geom_pointrange() +
	coord_flip() +
	geom_hline(aes(x=0), lty=2) +
	ylab(xlab) +
	xlab(ylab) #switch because of the coord_flip() above
	return(p)
	}
	# Create some dummy data.
	d <- data.frame(x = toupper(letters[1:10]),
	y = rnorm(10, .05, 0.1))
	d <- transform(d, ylo = y-1/10, yhi=y+1/10)
	forestplot(d)

view raw forestplot.r hosted with ❤ by GitHub

And here's what you get:

Thanks for sharing the code, Abhiji!