Mr.Herv? Pag?s Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 P.O. Box 19024 Seattle, WA 98109-1024 Dear Sir, I would like to find the SNPs density located in human gene transcript regions i.e. 5'UTR, 3'UTR, CDS or coding exon from the total SNP count (30443455) located at dbSNP Build 132. For this I have already downloaded the 3'UTR, 5'UTR and CDS from the UCSC table genome browser. Could I do it with SNPBLAST or ENTREZ SNP Database but SNPBLAST is not supporting what I want. Could you please tell me how would I proceed to obtain my goal. I would be glad for your kindness and assistance. Warm regards, Haojam Rocky Ph.D. scholar Seoul National University College of Medicine [[alternative HTML version deleted]]

Hi Haojam, On 01/05/2011 08:57 PM, ??? ? wrote: > Mr.Hervé Pagès > Program in Computational Biology > Division of Public Health Sciences > Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N, M2-B876 > P.O. Box 19024 > Seattle, WA 98109-1024 > > Dear Sir, > I would like to find the SNPs density located in human gene transcript > regions i.e. 5'UTR, 3'UTR, CDS or coding exon from the total SNP count > (30443455) located at dbSNP Build 132. For this I have already > downloaded the 3'UTR, 5'UTR and CDS from the UCSC table genome browser. > Could I do it with SNPBLAST or ENTREZ SNP Database but SNPBLAST is not > supporting what I want. If you are asking me if you could do this with SNPBLAST or ENTREZ SNP Database, well I don't know. I don't use those tools. Did you try to ask directly to the people supporting/distributing those tools? If you do so, you will need to be much more specific than "SNPBLAST is not supporting what I want". In particular, people will typically expect you to show what you've done so far, how you did it, what worked, what didn't, etc... > Could you please tell me how would I proceed to > obtain my goal. I would be glad for your kindness and assistance. I'm sure there must be many ways to do this. Following the same kind of approach as described in this recent thread https://stat.ethz.ch/pipermail/bioconductor/2010-December/036741.html would probably work for this too. (Be aware that this thread is continued in January 2011 and, unfortunately, navigating a thread by clicking the "Next message" link doesn't cross month boundaries :-( ) However, pulling all the SNPs from SNPlocs.Hsapiens.dbSNP.20101109 into a single GRanges object and finding the overlaps with the human 5'UTR, 3'UTR and CDSs might be putting too much stress on your hardware so this is a situation where you will benefit a lot from working one chromosome at a time. Something along the line of (pseudo-code, not tested): library(GenomicFeatures) ### Use the 'tablename' argument to pickup the exact transcript ### annotations you want. Also have a look at ### ?makeTranscriptDbFromBiomart for another source of ### annotations. txdb <- makeTranscriptDbFromUCSC("hg19") cdsbytx <- cdsBy(txdb, by="tx", use.names=TRUE) utr5bytx <- fiveUTRsByTranscript(txdb, use.names=TRUE) utr3bytx <- threeUTRsByTranscript(txdb, use.names=TRUE) ### Note that the lengths of the above 3 GRangesList objects ### differ because some transcripts don't have a 5' UTR or a ### 3' UTR or both. countSNPsByFeature <- function(txdb) { cdsbytx <- cdsBy(txdb, by="tx") utr5bytx <- fiveUTRsByTranscript(txdb) utr3bytx <- threeUTRsByTranscript(txdb) ans <- c(cds=0L, utr5=0L, utr3=0L) library(SNPlocs.Hsapiens.dbSNP.20101109) allchroms <- names(getSNPcount()) for (seqname in allchroms) { snps <- getSNPlocs(seqname, as.GRanges=TRUE) seqnames(snps) <- sub("ch", "chr", seqnames(snps)) seqnames(snps) <- sub("chrMT", "chrM", seqnames(snps)) n1 <- sum(countOverlaps(snps, cdsbytx)) n2 <- sum(countOverlaps(snps, utr5bytx)) n3 <- sum(countOverlaps(snps, utr3bytx)) ans <- ans + c(n1, n2, n3) } ans } Then: snpcount <- countSNPsByFeature(txdb) Don't know how long this would take, 15 minutes? one hour? maybe more... Let us know. You might need at least 4GB of RAM for this to work in reasonable time. Note that some SNPs will be counted more than once because a SNP can hit more than one feature e.g. the 5' UTR of transcript A and the CDS of transcript B etc... Hope this can give you a start. Cheers, H. > > Warm regards, > Haojam Rocky > Ph.D. scholar > Seoul National University College of Medicine -- Hervé Pagès Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpages at fhcrc.org Phone: (206) 667-5791 Fax: (206) 667-1319