Analyzing dendograms??
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 Number of attachments included with this message: 0 This message (and any associated files) is confidential and\...{{dropped}}