Hi there,
I have a long standing unresolved question about the difference between heatmap.2 and pheatmap.
In general, we could see the clusters produced by pheatmap exhibit a more obvious color pattern (the genes with the similar colors in each row will cluster together first) rather than heatmap.2 (the genes with the similar colors are distributed).
Does it mean pheatmap outperform heatmap.2 in terms of gene expression profile cluster analysis?
Sometimes, even the clusters of samples look different.
Does anyone know if heatmap.2 usually generate a less clear pattern for the gene expression profiles, why should we use it for the analysis?
Many thanks,
Tom
Both packages provide dozens of parameters for customization, and may have different defaults. I bet one can tweak both to produce very similar heatmaps. Personal preference and effort at reading documentation will have a lot of influence on ones results.
As @h.mon said, you can change the clustering algorithms for each quite easily - you should be able to derive essentially the same heatmap from each with a few tweaks. Both are fine for heatmap generation of expression data. It sounds like you might not be scaling by row or just not clustering the columns in your heatmap.2 call.
I always have issues getting multiple pheatmap plots in a single PDF from jupyter notebook, so I tend to avoid it, but it's really just personal preference.