""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
At 15:20 2004-01-05 +0000, Simon Fear wrote:
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: [EMAIL PROTECTED] web: http://www.synequanon.com
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