Hi, Please also note that seq(along=x) is almost always preferable to 1:length(x) and seq_len(n) to 1:n. (But as Sean says, if possible, and certainly in your case, using vectorized idioms is of course even more preferable.) Best wishes Wolfgang Sean Davis scripsit 16/03/2008 16:38: > On Sun, Mar 16, 2008 at 11:56 AM, JUAN MIGUEL MARIN DIAZARAQUE > <jmmarin at="" est-econ.uc3m.es=""> wrote: >> Hello, >> >> In previous message I wonder how to extract just the expressions of 102 >> genes under two conditions after a multtest procedure. >> >> At last, I wrote this unelegant code that seems to work: >> >> quedan <- resT[res$adjp[,"BH"]<0.05,] >> busco <- dimnames(quedan)[[1]] >> >> cosa <- NULL >> for (i in 1:length(dimnames(exprs(esetSub))[[1]])) >> for (j in 1:length(busco)) >> if (dimnames(exprs(esetSub[i,]))[[1]] == busco[j]) { >> cosa <- rbind(cosa, as.data.frame(exprs(esetSub))[i,]) } >> end >> end > > Generally, you can subset ExpressionSets just like you do data frames; > rows are genes or probes and columns are samples. If esetSub is what > you used for your multtest procedure, you should be able to do: > > exprs(esetSub)[res$adjp[,'BH']<0.05,] > > In general, for loops are quite useful in R, but for things like > subsetting or vectorized operations, it is better to look for other > alternatives as they are likely to be faster. > > Sean > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Best wishes Wolfgang ------------------------------------------------------------------ Wolfgang Huber EBI/EMBL Cambridge UK http://www.ebi.ac.uk/huber

Hello Sean, thank you very much, the command works fine. It is, by very far, faster than the for-option... Best > On Sun, Mar 16, 2008 at 11:56 AM, JUAN MIGUEL MARIN DIAZARAQUE > <jmmarin at="" est-econ.uc3m.es=""> wrote: >> Hello, >> >> In previous message I wonder how to extract just the expressions of 102 >> genes under two conditions after a multtest procedure. >> >> At last, I wrote this unelegant code that seems to work: >> >> quedan <- resT[res$adjp[,"BH"]<0.05,] >> busco <- dimnames(quedan)[[1]] >> >> cosa <- NULL >> for (i in 1:length(dimnames(exprs(esetSub))[[1]])) >> for (j in 1:length(busco)) >> if (dimnames(exprs(esetSub[i,]))[[1]] == busco[j]) { >> cosa <- rbind(cosa, as.data.frame(exprs(esetSub))[i,]) } >> end >> end > > Generally, you can subset ExpressionSets just like you do data frames; > rows are genes or probes and columns are samples. If esetSub is what > you used for your multtest procedure, you should be able to do: > > exprs(esetSub)[res$adjp[,'BH']<0.05,] > > In general, for loops are quite useful in R, but for things like > subsetting or vectorized operations, it is better to look for other > alternatives as they are likely to be faster. > > Sean > jm~ _______________________________ Juan Miguel Marin http://www.est.uc3m.es/jmmarin Dep. of Statistics University Carlos III of Madrid Spain (E.U.)