Over at the Molecular Ecologist, guest contributor Arianne Albert walks through how to make heatmap figures in R.
Heatmaps are incredibly useful for the visual display of microarray data or data from high-trhoughput sequencing studies such as microbiome analysis. Basically, they are false colour images where cells in the matrix with high relative values are coloured differently from those with low relative values. Heatmaps can range from very simple blocks of colour with lists along 2 sides, or they can include information about hierarchical clustering, and/or values of other covariates of interest. Fortunately, R provides lots of options for constructing and annotating heatmaps.
I’ve personally used heatmap graphics for visualizing population structure in a sample, or linkage disequilibrium along a stretch of genetic sequence, but I haven’t done anything very complex. Arianne’s examples use a data set that’s freely available on Dryad, and she includes a lot of step-by-step detail to build up complex figures—if you’re going to be visualizing some microarrary results or metagenomics data any time soon, you should read the whole thing, and probably bookmark it.◼