[BioC] Clustering in R

Johan Lindberg johanl at biotech.kth.se
Thu Jun 17 08:52:29 CEST 2004

Hi Wayne.

A couple of months ago I tried to deal with the same issues as you
probably do today. I found no good answers to how to cluster genes in R
in a way to get something useful out of it if you have a large set of
genes. In order to see some details in a dendrogram with 14000genes one
would have to have a heck of a screen as large as a house. I suggest you
use MEV from TIGR or some other freeware tool out there to do the job
for you. I use MEV myself after normalizing and preparing my data in R.

// Johan

Johan Lindberg
Royal Institute of Technology 
AlbaNova University Center
Stockholm Center for Physics, Astronomy and Biotechnology
Department of Molecular Biotechnology
106 91 Stockholm, Sweden



-----Original Message-----
From: bioconductor-bounces at stat.math.ethz.ch
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of
wmak at brandeis.edu
Sent: den 16 juni 2004 22:26
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] Clustering in R

Dear list members,

I'm an undergrad and I work in a lab at Brandeis.  I am trying to
around 14,000 genes across 6 microarray experiments.  Two of these
are replicates.  I have decided to use R since it seems to be the most
complete and flexible software package for normalization and clustering
microarray data.

The problem is that I am new to clustering and to R.  Just to mention of
a few
of the problems I'm having: the dendrogram that is drawn by R from the
object is far too dense to see any of the gene names; kmeans won't work,
returning an error saying that my data has NAs in it (there weren't any
missing values in the original table though); I'd like to be able to see
heatmap or a cumulative plot of expression profiles for genes that are
clustered together or are on the same branch of the dendrogram.

I know that these questions are probably very simple, but I can't seem
to find
the answer to them online or in the documentation.  If anyone can answer
questions or direct me toward resources that deal with clustering in R
BioConductor, a basic tutorial that takes a practical approach to it, I
really appreciate it.  Any other reading material that isn't too heavy
statistics that deals with clustering for that matter, would be very

Thank you in advance,

Wayne Mak

Bioconductor mailing list
Bioconductor at stat.math.ethz.ch

More information about the Bioconductor mailing list