Here is what dChip manual says: "The default clustering algorithm of genes is as follows: the distance between two genes is defined as 1 - r where r is the Pearson correlation coefficient between the standardized expression values (make mean 0 and standard deviation 1) of the two genes across the samples used. Two genes with the closest distance are first merged into a super-gene and connected by branches with length representing their distance, and are then excluded for subsequent merging events. The expression values of the newly formed super-gene is the average of standardized expression values of the two genes (centroid-linkage) across samples. Then the next pair of genes (super-genes) with the smallest distance is chosen to merge and the process is repeated n – 1 times to merge all the n genes. A similar procedure is used to cluster samples....." so, to follow that exactly, what you need to do is something like: row.dist <- as.dist(1 - cor(scale(t(esetSub2X)))) col.dist <- as.dist(1 - cor(scale(esetSub2X))) heatmap(esetSub2X, Colv=as.dendrogram(hclust(col.dist, method="centroid")), Rowv=as.dendrogram(hclust(row.dist, method="centroid"))) ====================================================================== ===================== > Message: 20 > Date: Tue, 16 Nov 2004 09:05:30 -0000 > From: "michael watson (IAH-C)" <michael.watson@bbsrc.ac.uk> > Subject: RE: [BioC] How can I get Heatmap using dChip > clustering..which is nice& easy to see patterns > To: <saurin_jani@yahoo.com>, "Bioconductor Bioconductor" > <bioconductor@stat.math.ethz.ch> > Message-ID: > <8975119BCD0AC5419D61A9CF1A923E95E89817@iahce2knas1.iah.bbsrc. reserved> > > Content-Type: text/plain; charset="us-ascii" > > Hi Saurin > > I may be wrong, but it looks like your code calculates the euclidean > distance between rows of 1-cor(), which is itself a distance matrix of > sorts. Try: > > row.dist <- as.dist(1 - cor(t(esetSub2X))) > col.dist <- as.dist(1 - cor(esetSub2X)) > heatmap(esetSub2X, Colv=as.dendrogram(hclust(col.dist, > method="average")), Rowv=as.dendrogram(hclust(row.dist, > method="average"))) > > Mick > > -----Original Message----- > From: Saurin Jani [mailto:saurin_jani@yahoo.com] > Sent: 15 November 2004 23:28 > To: Bioconductor Bioconductor > Subject: [BioC] How can I get Heatmap using dChip clustering..which is > nice& easy to see patterns > > > Hi , > > How can I get dChip clustering on heatmap?..which is > nice & easy to see patterns. > > I am using 1- cor(eset) but somehow its not working I > am still getting diff. kind of clustering dendrogram. > > > d <- dist((1 - cor(esetSub2X)),method = > "euclidean"); > > dCol <- dist(t((1- cor(esetSub2X))),method = > "euclidean"); > > > heatmap(esetSub2X,Colv= > as.dendrogram(hclust(d,method = "complete")),Rowv = > NA,col = rbg,cexRow = 1,cexCol = 1); > > > Am I missing something? > > Any heatmap clustering is helpful. > > Thank you, > Saurin > > > > __________________________________ > > The all-new My Yahoo! - Get yours free! > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > > > > ------------------------------