[BioC] Clustering like Eisen

Stephen Henderson s.henderson at ucl.ac.uk
Wed Aug 18 10:06:06 CEST 2004



plot(hc, hang=-1, labels=A.suitable.vector)

this will give you a complete clustering of samples with the euclidean
distance. This is fine for rma data that is already in log2 units.

You can change the clustering "method" of hclust check ?hclust, or you can
use a different distance method something like 1-cor, but you will have to
then convert it to a distance metric using 

my.metric<- 1-cor(exprs(Your.exprSet))

or something like that

-----Original Message-----
From: mcolosim at brandeis.edu
To: bioconductor at stat.math.ethz.ch
Sent: 17/08/04 23:34
Subject: [BioC] Clustering like Eisen

Is there a way to create a dendrogram of arrays(samples) like the Eisen
et al
method used in dChip? I don't want a heatmap, just the clustering of

I tried kmeans but that doesn't produce something I can plot as a



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