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Old 07-08-2014, 12:41 PM   #1
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Location: USA

Join Date: Sep 2012
Posts: 130
Default Improving heatmap plots

I sometimes make heatmaps for gene expression data. I proceed with the basic heatmap.2 method (based on DESeq recommendation):
heatmap.2( x, scale="row", trace="none",
dendrogram="both", Rowv=TRUE, Colv=TRUE, col = col )
Based on all the parameters, it should come out okay. However, very often I find that the resulting heatmap does not cluster very well. For a simple two-group experiment, if I give it some differentially expressed genes, I would expect to see the heatmap divided into four sections (up and down for each condition). In my experience, that result has been very difficult to achieve.

Based on heatmap.2 documentation, it seems to be very flexible, but there are a lot of options. Has anyone been able to significantly improve their clustering by adjusting various parameters? Is there a particular combination that works especially well for gene expression data?
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