heatmap.2 row clustering does not look right

Question

[moxu]

Image is at https://imgur.com/CDzSiLU

I am using R heatmap.2.

Take a look at the above heatmap generated by heatmap.2. There are 5 big clusters of rows: 1 yellow/red, 2 red/yellow, 3 yellow/red, 4 red/yellow, 5 yellow/red.

Shouldn't the yellow/red clusters cluster together, and red/yellow ones cluster together, and then form the biggest cluster?

The R code is as follows:

heatmap.2(data.matrix(heatmapEntries), main="xxx", dendrogram="row", Rowv = TRUE, Colv=FALSE, margins=c(11.3333333333333,5), scale="row", trace = "none", cexRow=1, lhei=c(1,10), lwid=c(1,3));

Thanks in advance!

Answer 1

[Kevin Blighe]

Not necessarily, but you can modify the ordering of the heatmap with the reorderfun parameter to heatmap.2. For example, try:

heatmap.2(..., reorderfun=function(d,w) reorder(d, w, agglo.FUN=mean), ...)

You can choose any mathematical parameter here, including min, max, var, sd, etc.

---

You can also modify the scaling to see how that modifies the heatmap ordering. For example, to scale to Z-scores (by gene), use:

heatZ <- t(scale(t(heatmapEntries)))

heatmap.2(data.matrix(heatZ),
  ...,
  scale = 'none',
  reorderfun = function(d,w) reorder(d, w, agglo.FUN=mean),
  ...)

---

For other suggestions, see my answer here: A: How to cluster the upregulated and downregulated genes in heatmap?

[moxu]

Scaling is the answer! Thanks much!

[Kevin Blighe]

Okay, but, as per the other thread, scaling is usually combined with a 'breaks' parameter:

heatZ <- t(scale(t(heatmapEntries)))
myBreaks <- seq(-3, 3, length.out=101)
heatmap.2(data.matrix(heatZ), ..., breaks=myBreaks, scale="none", reorderfun=function(d,w) reorder(d, w, agglo.FUN=mean), ...)

Also important to realise that the heatmap / hierarchical clustering is just for the purposes of visualisation. The genes that you supplied to your heatmap would have presumably been derived from expression data on a different scale (if RNA-seq, most like negative binomial).