[BioC] SOM clustering

[Straubhaar, Juerg]

I used this code, taken from http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#R_clustering, the very helpful, for all kinds of things, manuals by T. Gierke at University of California Riverside.

library(som) # Loads the required SOM library.
y <- matrix(rnorm(50), 10, 5, dimnames=list(paste("g", 1:10, sep=""), paste("t", 1:5, sep=""))) # Creates a sample data set.
y <- t(scale(t(y))) # Normalizes the data so that each row has a mean close to zero and a standard deviation of one.
y.som <- som(y, xdim = 5, ydim = 6, topol = "hexa", neigh = "gaussian") # Performs SOM clustering.
plot(y.som) # Plots SOM clustering result.
y.som$visual # Provides the assignment of rows items to the SOM clusters. Remember that the coordinate counting starts here at zero!

Juerg

________________________________________
From: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] On Behalf Of Tanay Ghosh [guest] [guest at bioconductor.org]
Sent: Tuesday, February 07, 2012 12:08 PM
To: bioconductor at r-project.org; tanay.ghosh at inserm.fr
Subject: [BioC] SOM clustering

How can I generate SOM clustering from my microarray data and how to see a dendogram view of SOM clustering?

 -- output of sessionInfo():

> sessionInfo()
R version 2.14.0 (2011-10-31)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] class_7.3-3

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