You keep the genes where at least 2 samples have a cpm greater than 100. rowSums(cpm(d) >100) counts, for each gene (row), how many samples have a cpm >= 100. Kasper On Wed, Nov 28, 2012 at 10:54 PM, Steve Lianoglou <mailinglist.honeypot at="" gmail.com=""> wrote: > Hi, > > On Wed, Nov 28, 2012 at 10:14 PM, Vittoria Roncalli <roncalli at="" hawaii.edu=""> wrote: >> Hi, >> >> I would like to understand how the filter of low expression tags works. If >> I run the command >> >>>keep <- rowSums (cpm(d)>100) >=2 >> d <- d[keep,] >> dim(d) >> >> as in the use guide page 32, this means that I am using a cutoff of 100cpm, >> but how are treated the 2 samples? Did are they averaged and then the low >> tags are removed? >> Is each sample considered separate and filtered by itself? >> Thanks foe the help in advance > > How many samples (columns) do you have? > > You should first look at the output of `cpm(d) > 100` to see what you > are getting -- this will be a logical (boolean) matrix that has the > same dimensionality as `cpm(d)`. > > rowSums( a logical matrix ) > > returns a vector that is as long as there are rows in the logical > matrix, and each value indicates how many columns are TRUE in that > row. > > HTH, > -steve > > -- > Steve Lianoglou > Graduate Student: Computational Systems Biology > | Memorial Sloan-Kettering Cancer Center > | Weill Medical College of Cornell University > Contact Info: http://cbio.mskcc.org/~lianos/contact > > _______________________________________________ > 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