dendrograms in clustergram vs pdist->lin​kage->dend​rogram

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Diego
Diego on 11 Oct 2012
Hello,
Can somebody explain why the dendrogram produced by clustergram is different than the one obtained by the traditional pdist, linkage and dendrogram process?
As I understand clustergram uses Euclidean distance metric and Average linkage. But when I run this functions with the aforementioned parameters the resultant groups are different than those displayed by clustergram.
How can I reproduce the same dendrogram produced by clustergram using the pdist->linkage->dendrogram approach?
Thanks in advance.
  1 Comment
Diego
Diego on 11 Oct 2012
I thought this could be explained by the standardization performed by clustergram.
However, I use zscore for both, the matrix and each column in the matrix and the dendograms are still different than those of clustergram.
Any idea is much appreciated.

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Answers (1)

Lucio Cetto
Lucio Cetto on 11 Oct 2012
Clustergram standardizes the data. I am not sure what release you are using but the way you control this option with the input arguments to clustergram has not been consistent. Also clustergram runs optimal-leaf-order.
HTH
Lucio
  1 Comment
Diego
Diego on 11 Oct 2012
Thank you Lucio. Yes the optimalleaforder can be an explanation. I'm a little bit rusty in matlab and also it's my first time handling a Class. So it can take me sometime to perform the tests.
Thanks again.
Diego

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