That said, there are a number of differential coexpression papers out there noting that, among the remaining transcripts, calculating (shrunken or unshrunken) estimates of the covariance matrices can be... interesting. 'corpcor', 'glasso', 'huge', and 'WGCNA' may come in handy for the latter task, with WGCNA explicitly designed for finding differential coexpression. The authors of one such (throwaway -- no implementation released) paper note that they crammed 128GB of physical RAM into the machine used for the analyses in the paper, but it's quite possible the authors did not realize that filtering could have saved them a lot of time and memory. On Fri, Sep 9, 2011 at 3:08 AM, Sean Davis <sdavis2@mail.nih.gov> wrote: > Hi, January. > > One common way of reducing the number of features is to choose the top > X% by variance or coefficient of variation. A large percentage of > genes are not even expressed in a given tissue type and another large > percentage do not vary across a sample set. You can use the > genefilter package to perform such filtering. > > Sean > > On Wed, Sep 7, 2011 at 5:29 PM, January Weiner <january.weiner@gmail.com> > wrote: > > Hello, > > > > I'm struggling with co-expression analysis, and for that I would like > > to try to cluster all the genes I have in my microarray set, including > > those which are not differentially expressed between the study groups. > > I am using CoXpress at the moment and will try my luck with GSCA as > > well, but both packages seem to have been layed out for 3000 rather > > than 30000 genes. > > > > How do you do that in R? I get errors about R not being able to > > allocate enough memory. Clearly, the amount of memory required to > > calculate all correlations the simple way might be a bit on the large > > side, but I can think of one or two tricks to get this done; I wonder > > whether it has been implemented already. > > > > Other than that -- how should I reasonably limit the number of genes > > to study? i don't want to bias the outcome of the analysis by > > selecting only genes that are DE, actually -- I would be very > > interested in genes that show differential co-expression, but no > > differences in expression. > > > > Kind regards, > > > > j. > > > > -- > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor@r-project.org > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- If people do not believe that mathematics is simple, it is only because they do not realize how complicated life is. John von Neumann<http: www-groups.dcs.st-="" and.ac.uk="" ~history="" biographies="" von_neumann.html=""> [[alternative HTML version deleted]]