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

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Diego
Diego 2012-10-11
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.
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Diego
Diego 2012-10-11
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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回答（1 个）

Lucio Cetto
Lucio Cetto 2012-10-11
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 个评论
Diego
Diego 2012-10-11
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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