I've been following the DESeq2 workflow for analyzing RNAseq expression data. After using the `rlog` function to transform my data, I plotted a heatmap as follows:
# rlog transformation rld <- rlog(dds, blind=FALSE) # plot the rlog transformed samples sampleDists <- dist( t( assay(rld) ) ) sampleDistMatrix <- as.matrix( sampleDists ) rownames(sampleDistMatrix) <- rld$reactor colors <- colorRampPalette( rev(brewer.pal(9, "Blues")) )(255) pheatmap(sampleDistMatrix, clustering_distance_rows=sampleDists, clustering_distance_cols=sampleDists, col=colors)
How do I best interpret the scale of the resulting heatmap? I noticed that there seems to be no specific upper bound. Does anyone have a suggestion for how to transform the data in the heatmap further so that the scale goes from 0 to 1?