Question: How can I get Heatmap using dChip clustering

0

Shi, Tao •

**720**wrote: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
>
>
>
> ------------------------------