Analyzing dendograms??

Id like to thank you guys how have taken the time to look into my problem. 
I think the question drifted away from my original question as Simon Fear 
said. What I wanted to know was the following:

""I have used heatmap to visualize my microarray data. I have a matrix of 
M-values. I do the following.

#The distance between the columns.
sampdist <- dist(t(matrix[,]), method="euclidean")
sclus <- hclust(sampdist, method="average")
#The distance between the rows.
genedist <- dist(matrix[,], method="euclidean")
gclus <- hclust(genedist, method="average")
heatmap(matrix[,],Rowv=as.dendrogram(gclus),Colv=as.dendrogram(sclus), col=rbg)

So far so good. But what if I want to look at a group of genes that appear 
to have the same expression pattern in the heatmap? How do I zoom in on a 
dendogram in a heatmap to look at which genes that are forming the 
interesting clusters? I would really appreciate if someone could give me a 
pointer.""

But since I did not get any good answers of how to analyze 
dendograms/heatmaps/hclust in R in a proper way I ask myself, is there a 
way of doing this in R? or is this a limitation of the functions available 
today in the R programming language. I know there are some functions like 
cutree etc but the documentation is really, really sparse. Are there any 
tutorials out there of how to do these things? or should one turn to 
alternative programs like MEV from TIGR?

A confused mind looking for answers..

/ J

Post script: I'm afraid my `solution` was no good, because
I forgot the need to change nc and nr. (I got bogged down
in passing ylim and lost track of your real question.)

Hopefully someone with a deeper understanding of the
original problem will come to the rescue. If not there may
be milage on restricting your matrix[,] to matrix[<cond1>,<cond2>]
according to information in sclus and gclus. But I am in
over my depth here.

On Sun, 4 Jan 2004, Johan Lindberg wrote:

I have used heatmap to visualize my microarray data. I

have a matrix of

M-values. I do the following.

#The distance between the columns.
sampdist <- dist(t(matrix[,]), method="euclidean")
sclus <- hclust(sampdist, method="average")
#The distance between the rows.
genedist <- dist(matrix[,], method="euclidean")
gclus <- hclust(genedist, method="average")

heatmap(matrix[,],Rowv=as.dendrogram(gclus),Colv=as.dendrogram
(sclus),

col=rbg)

So far so good. But what if I want to look at a group of

genes that appear

to have the same expression pattern in the heatmap? How

do I zoom in on a

dendogram in a heatmap to look at which genes that are forming the
interesting clusters? I would really appreciate if

someone could give me a

pointer.

Simon Fear
Senior Statistician
Syne qua non Ltd
Tel: +44 (0) 1379 644449
Fax: +44 (0) 1379 644445
email: Simon.Fear at synequanon.com
web: http://www.synequanon.com

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Johan Lindberg
Royal Institute of Technology
AlbaNova University Center
Stockholm Center for Physics, Astronomy and Biotechnology
Department of Molecular Biotechnology
106 91 Stockholm, Sweden

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