On 5/31/06 2:25 AM, "Ron Ophir" <ron.ophir at="" weizmann.ac.il=""> wrote: > I see. I missed it. You mean something like this > > x<-matrix(rnorm(1000,10,2),100,100) > hc<-as.dendrogram(hclust(dist(x,method="euclidean"))) > hr<-as.dendrogram(hclust(as.dist(cor(x,method="pearson")))) > x11();hv <- heatmap(x,Rowv=hr,Colv=hc) Couldn't have (and, indeed, didn't) said it better myself. Sean >>>> Sean Davis <sdavis2 at="" mail.nih.gov=""> 30/05/2006 22:02:16 >>> > > > > On 5/30/06 3:56 PM, "Ron Ophir" <ron.ophir at="" weizmann.ac.il=""> wrote: > >> I would like to run clustering on columns (samples) and rows (genes) > and >> get a plot similar to the output of heatmap(). However I would like > to >> apply euclidean distance to samples and pearson distance to genes. >> Is it possible to do it with heatmap(). If not, is there other > function >> that can do it? > > Ron, > > You can pass Rowv and Colv dendrogram objects, as output by hclust, > for > example. By doing so, you can use different distance functions (or > even > different clustering algorithms) for the rows and columns. > > Sean