Dear Martin, Thank you very much for your help. It seems I have got it with your help. In fact, I have read the manual of IRanges a few days ago. But it is difficult to understand what is doing of methods flank, narrow, restrict, etc. I think the best written documents are bedtools. Just a complain. I will have a closer look again. Thanks. On Wed, Mar 16, 2011 at 2:25 PM, Martin Morgan <mtmorgan at="" fhcrc.org=""> wrote: > On 03/16/2011 01:46 AM, Fabrice Tourre wrote: >> >> Dear Martin, >> I am appreciated for you suggestion. >> I found in GenomicFeatures, there are such method: >> transcriptsBy, exonsBy, cdsBy, intronsByTranscript, >> fiveUTRsByTranscript, threeUTRsByTranscript. >> >> So maybe I can used these method to got the coverage on exons, cds, >> transcripts, introns, 3'utr and 5'utr. Do you have some ideas how to >> got the coverages on promoter regions? For example, up to TSS 5kb >> regions. > > Hi Fabrice -- if you have the TSS (e.g., from start(transcriptsBy(<...))), > you can easily create GRanges representing them, either directly using > ?GRanges or ?GRangesList, or by manipulating an existing GRanges / > GRangesList object with commands like flank, narrow, etc., as documented on > for instance the GRanes help page. Martin > >> Thanks. >> >> On Tue, Mar 15, 2011 at 9:17 PM, Martin Morgan<mtmorgan at="" fhcrc.org=""> ?wrote: >>> >>> On 03/15/2011 12:19 PM, Fabrice Tourre wrote: >>>> >>>> What's more, how many covaged the repeat region and unique region? >>> >>> Hi Fabrice -- >>> >>> The steps in the work flow might invovle: input reads >>> >>> ?library(GenomicRanges) >>> ?aln<- readGappedAlignemnts(<...>)) >>> >>> and create regions of interest, e.g., from >>> >>> ?library(GenomicFeatures) >>> ?txdb<- makeTranscriptDbFromUCSC(<...>) >>> ?cds<- cdsBy(txdb, "gene") >>> >>> or using the biomaRt or AnnotationDbi packages. Then count reads in each >>> region of interest >>> >>> ?hits<- countOverlaps(aln, cds) >>> >>> or calculate coverage and take views based on your regions of interest >>> >>> ?cvg<- coverage(aln) >>> ?v<- Views(cvg, ranges(cds)) >>> >>> and then summarize, e.g., viewSums. Maybe others will contribute more >>> detail. >>> >>> Martin >>> >>>> >>>> On Tue, Mar 15, 2011 at 8:18 PM, Fabrice Tourre<fabrice.ciup at="" gmail.com=""> >>>> ?wrote: >>>>> >>>>> Dear list, >>>>> I am analysis mouse MeDIP-seq data, I want to know what percent reads >>>>> coveraged the promter, 3'UTR, 5'UTR, intron and Exon region. Is there >>>>> any packages can do this? >>>>> Thank you very much in advance. >>>>> >>>> >>>> _______________________________________________ >>>> 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 >>> >>> >>> -- >>> Computational Biology >>> Fred Hutchinson Cancer Research Center >>> 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109 >>> >>> Location: M1-B861 >>> Telephone: 206 667-2793 >>> >>> _______________________________________________ >>> 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 >>> > > > -- > Computational Biology > Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109 > > Location: M1-B861 > Telephone: 206 667-2793 > > _______________________________________________ > 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 >