[BioC] How can I get Heatmap using dChip clustering

[Shi, Tao]

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 at bbsrc.ac.uk>
> Subject: RE: [BioC] How can I get Heatmap using dChip
> 	clustering..which is	nice& easy to see patterns
> To: <saurin_jani at yahoo.com>,	"Bioconductor Bioconductor"
> 	<bioconductor at stat.math.ethz.ch>
> Message-ID:
> 	<8975119BCD0AC5419D61A9CF1A923E95E89817 at 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 at 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
> 
> 
> 		
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