It might be reasonable to split on space (" "), then paste/collapse together with "" and then split on ",". This will ensure that all spaces (before or after comma) are removed at once. Oleg Martin Morgan wrote: > Hi Paul -- I saw this on the R mailing list, too. Such > 'cross-posting' is discouraged (though in this case you get answers > that you wouldn't have got if you'd restricted yourself to just one > list!) > > I wonder if your problem was splitting the 'genes' character string > with "," rather than ", *" or ",[[:blank:]]*" ? Whatever the case, if > you have a data frame (from jim holtman's reply on the R list) > >> func_gen > Function x > 1 Function1 gene5, gene19, gene22, gene23 > 2 Function2 gene1, gene7, gene19 > 3 Function3 gene2, gene3, gene7, gene23 > > I would have created a named list associating function and gene name: > >> fids <- sapply(func_gen[["x"]], strsplit, ",[[:blank:]]*") >> names(fids) <- func_gen[["Function"]] > > and converted this to an incidence matrix: > >> uids <- unique(unlist(fids)) >> incidence <- sapply(fids, "%in%", x=uids) >> rownames(incidence) <- uids > > Since these seem like gene sets, and your work flow might continue > along these lines, it might be convenient to represent your data as a > gene set collection > >> library(GSEABase) >> gs <- mapply(GeneSet, fids, setName=names(fids)) >> gsc <- GeneSetCollection(gs) > > and then let the package do the clever operation > >> incidence(gsc) > gene5 gene19 gene22 gene23 gene1 gene7 gene2 gene3 > Function1 1 1 1 1 0 0 0 0 > Function2 0 1 0 0 1 1 0 0 > Function3 0 0 0 1 0 1 1 1 > > Martin > > Paul Christoph Schr?der <pschrode at="" alumni.unav.es=""> writes: > >> Hello all! >> >> I have the following problem with the %in% command: >> >> 1) I have a data frame that consists of functions (rows) and genes >> (columns). The whole has been loaded with the "read.delim" command >> because of gene-duplications between the different rows. >> 2) Now, there is another data frame that contains all the genes (only >> the genes and without duplicates) from all the functions of the above >> data frame. >> >> What I want to do now is to use the "% in %" command to obtain a >> TRUE-FALSE data frame. This should be a data frame, where for every >> function some genes are TRUE and some are FALSE depending if they were >> or not in the specific function when matched against the "all genes" >> data frame. >> >> The main problem I have is the way how the genes are in the first data >> frame. I used the "unlist" command to separate them through commas ",". >> But every time I do the match between the first and second data frame it >> returns out FALSE for every gene in every function. >> >> Can anyone please give me a hind how to handle the problem? >> Thank you very much in advance! >> >> Paul >> >> >> >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> 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 > -- Dr Oleg Sklyar * EBI-EMBL, Cambridge CB10 1SD, UK * +44-1223-494466