On Thu, Jun 26, 2014 at 9:53 AM, gregory voisin wrote: > Hi Valirie, > this is the code . > > I call my function: > > obj_build_list5 = mclapply(obj_build_list3, function(x) > {addconservedTFSInformation(x)} ,mc.cores =nbcores) > > > addconservedTFSInformation<- function(annot_chr){#annot_chr is a gr object > > > #load the initial TFS data and create a GRanges Obj > conservedTFSFile = as.data.frame(read.table()) > conservedTFS = GRanges(seqnames = conservedTFSFile$V2, ranges= > IRanges(conservedTFSFile$V3, conservedTFSFile$V4)) > mcols(conservedTFS)= conservedTFSFile[,c(5,7,8)] > colnames(mcols(conservedTFS)) = c("TS_name","TS_strand","Z_score") > The above lines are turning a GFF file into a GRanges. This is a common operation, so we have implemented it as: conservedTFS <- rtracklayer::import("../FullAnnotation450K/Annotation450KBuilder/data/conserved_TFBS_sites_ucsc_JUNE2014.gtf") > > > #add the metaColumn for the conservedTFS annotation > values(annot_chr) <- cbind(values(annot_chr), > DataFrame(conservedTFS_name = rep(NA, length(annot_chr)))) > values(annot_chr) <- cbind(values(annot_chr), > DataFrame(conservedTFS_position = rep(NA, length(annot_chr)))) > values(annot_chr) <- cbind(values(annot_chr), > DataFrame(conservedTFS_distance = rep(NA, length(annot_chr)))) > values(annot_chr) <- cbind(values(annot_chr), > DataFrame(conservedTFS_score = rep(NA, length(annot_chr)))) > values(annot_chr) <- cbind(values(annot_chr), > DataFrame(conservedTFS_strand = rep(NA, length(annot_chr)))) > > #add information for each CpG > for (j in 1:length(annot_chr)){ > #find overlap > ov_current = nearest(annot_chr[j],conservedTFS) > conservedTFS_current= conservedTFS[ov_current] > if(!(length(ov_current)==0)){ > mcols(annot_chr)[["conservedTFS_name"]][j] = > as.vector(mcols(conservedTFS_current[1])[["TS_name"]]) > mcols(annot_chr)[["conservedTFS_position"]][j] = > start(ranges(conservedTFS_current[1])) > mcols(annot_chr)[["conservedTFS_distance"]][j] = > start(ranges(conservedTFS_current[1]))- start(ranges(annot_chr[j])) > mcols(annot_chr)[["conservedTFS_score"]][j] = > as.vector(mcols(conservedTFS_current[1])[["Z_score"]]) > } > } > The nearest() function is vectorized, so you could do: n <- nearest(annot_chr, conservedTFS) To get the index of the nearest TFS to each annot_chr range, as a vector in the same order as annot_chr. Then merge the information like this: annot_chr$conservedTFS_name <- conservedTFS$name[n] annot_chr$conservedTFS_position <- start(conservedTFS)[n] annot_chr$conservedTFS_distance <- abs(start(conservedTFS)[n] - start(annot_chr)) annot_chr$conservedTFS_score <- conservedTFS$score[n] Hope this helps get you started, Michael > #save the object : one object by chromosome > nb= unlist(strsplit(chr, "chr"))[2] > name_obj = paste0(nb,".FullAnnotation450K_",nb, ".RData") > save (annot_chr, file = name_obj) > > #return > return(annot_chr) > } > > > > > Le Jeudi 26 juin 2014 12h04, Valerie Obenchain a > écrit : > > > > Hi, > > I think you mean the GRanges class. GenomicRanges is a virtual class, > GRanges is the concrete subclass. > > Please show a reproducable example of what you're trying to do. When you > provide an example, instead of asking for a apply function for GRanges, > others on the list can see what the end goal is and suggest > alternatives. Using an *apply function may not be the best approach. > > Valerie > > > > On 06/26/2014 06:41 AM, Maintainer wrote: > > Hello, > > > > Does the apply function exist for genomisRange object. Here , I don't > talk about a genomicRangesList object but genomic Range. > > Is it pertinent to implement it ? > > > > Actually, I populate my gr object with a for loops : depending the > position of the gene , I had some information in mcol( gr obj). > > unsurprising, the for loop is totally unefficient. > > > > Greg. > > Lady Davis Institute > > Montreal > > > > -- output of sessionInfo(): > > > >> > sessionInfo() > > R version 3.0.1 (2013-05-16) > > Platform: x86_64-redhat-linux-gnu (64-bit) > > > > locale: > > [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C > > [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 > > [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 > > [7] LC_PAPER=C LC_NAME=C > > [9] LC_ADDRESS=C LC_TELEPHONE=C > > [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C > > > > attached base packages: > > [1] parallel stats graphics grDevices utils datasets methods > > [8] base > > > > other attached packages: > > [1] ade4_1.6-2 IRanges_1.20.7 BiocGenerics_0.10.0 > > > > loaded via a namespace (and not attached): > > [1] stats4_3.0.1 tools_3.0.1 > > > > > > -- > > Sent via the guest posting facility at bioconductor.org. > > > > ________________________________________________________________________ > > devteam-bioc mailing list > > To unsubscribe from this mailing list send a blank email to > > devteam-bioc-leave@lists.fhcrc.org > > You can also unsubscribe or change your personal options at > > https://lists.fhcrc.org/mailman/listinfo/devteam-bioc > > > > > -- > Valerie Obenchain > Program in Computational Biology > Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N, Seattle, WA 98109 > > Email: vobencha@fhcrc.org > Phone: (206) 667-3158 > [[alternative HTML version deleted]] > > > _______________________________________________ > 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 > [[alternative HTML version deleted]]