Welcome to R. The learning curve is well worth the benefits. If you are used to Eisen clustering and other fancy softwares to do clustering, then you might be a little disappointed with R's clustering ability of thousands of genes. But then again clustering is an exploratory tool and I see no reason why it should be the only analysis that some papers on microarray seem to focus on. My own bias aside, there are functions called heatmap, hclust that might useful.
You might to check out the documentation and workshop section of BioConductor (http://www.bioconductor.org/) which have R packages designed for the analysis of genomic data. But you should definitely try to read the Introduction to R first http://cran.r-project.org/doc/manuals/R-intro.html and other documents. Regards, Adai On Wed, 2005-07-13 at 10:49 -0400, Baoqiang Cao wrote: > Dear All, > > Just start to use the long expected R, my focus will be > doing clustering on microarray data, just wonder, anyone can > show me any references to conquer the steep learning curve? > Thanks! > > Best regards, > Baoqiang Cao > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html