I want to do hierarchial clustering of a binary matrix having 13702 rows and 1345 columns? How can i do it in R using bioconductor or using R libraries. *Regards* *Swati Sinha* Ph.D Student *C*enter* *for* C*omputational* B*iology and* B*ioinformatics, *S*chool of* C*omputational* &* *I*ntegrative* S*ciences *J*awaharlal* **N*ehru *U*niversity, New Delhi-110067 [[alternative HTML version deleted]]

For binary data you could use the hamming/edit distance (implemented in the e1071 library) and then cluster with hclust. Other distance measures can be found/constructed in R with ?dist, ?corr, the bioDist library or search other libraries for more. # Here is an example for hierarchical clustering and plotting of binary data: library(e1071) # import your binary data with read.table or read.delim; the following # example uses random data y <- matrix(sample(c(0,1), 100, replace=TRUE), 10, 10, dimnames=list(paste("g", 1:10, sep=""), paste("t", 1:10, sep=""))) disma <- hamming.distance(y) hr <- hclust(as.dist(disma)) plot(as.dendrogram(hr), edgePar=list(col=3, lwd=4), horiz=T) Thomas On Sun, Dec 19, 2010 at 01:17:35AM +0530, Swati Sinha wrote: > I want to do hierarchial clustering of a binary matrix having 13702 rows and > 1345 columns? > > How can i do it in R using bioconductor or using R libraries. > > *Regards* > *Swati Sinha* > Ph.D Student > *C*enter* *for* C*omputational* B*iology and* B*ioinformatics, > *S*chool of* C*omputational* &* *I*ntegrative* S*ciences > *J*awaharlal* **N*ehru *U*niversity, > New Delhi-110067 > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor