this is terrific, thanks so much Herve
--t

2011/9/28 Hervé Pagès <hpages@fhcrc.org>

> Hi Shirley,
>
>
> On 11-09-22 02:24 PM, Hervé Pagès wrote:
>
>> Hi Shirley,
>>
>> On 11-09-22 11:29 AM, shirley zhang wrote:
>>
>>> Dear All,
>>>
>>> I am planing to map the SNPids to hg18 positions (chr and position)
>>> for a huge list of human snps. I've tried the package
>>> "SNPlocs.Hsapiens.dbSNP.**20090506" and have 2 questions regarding this
>>> package:
>>>
>>> 1. Do the SNPs in this package map the hg18 genome (NCBI Build 36.3
>>> with Group Label "reference" instead of "Celera" or "HuRef"?
>>>
>>
>> Yes, they are mapped to hg18. See:
>>
>>
>> http://bioconductor.org/**packages/release/data/**
>> annotation/html/SNPlocs.**Hsapiens.dbSNP.20090506.html<http://bioconductor.org/packages/release/data/annotation/html/SNPlocs.Hsapiens.dbSNP.20090506.html>
>>
>>
>> and the man page of the package for additional details:
>>
>>  > library(SNPlocs.Hsapiens.**dbSNP.20090506)
>>  > ?SNPlocs.Hsapiens.dbSNP.**20090506
>>
>>
>>> 2. If I don't know the chr information (seqname), can I obtain the
>>> position with dbSNP Id only?
>>>
>>
>> Unfortunately, because SNPs are stored in one data frame per
>> chromosome, if you don't know the chr then you need to load and
>> query each data frame individually.
>>
>> With more recent SNPlocs packages (e.g.
>> SNPlocs.Hsapiens.dbSNP.**20100427), provision was added to
>> let the user load SNPs from more than 1 chromosome in a single
>> GRanges object, so you can do something like:
>>
>> ## Load all the SNPs in a big GRanges object (takes about
>> ## 13 minutes and requires 6GB of RAM!):
>> all_snps <- getSNPlocs(names(getSNPcount()**), as.GRanges=TRUE)
>>
>> ## Use the rs ids to set the names (takes about 6 minutes):
>> names(all_snps) <- paste("rs", elementMetadata(all_snps)$**RefSNP_id,
>> sep="")
>>
>> ## Then extract your SNPs from the big GRanges object (again,
>> ## this can take a long time, depending on how many SNPs you
>> ## extract):
>> my_rs_ids <- sample(names(all_snps), 1000)
>> my_snps <- all_snps[my_rs_ids]
>>
>> However, please note that, starting with
>> SNPlocs.Hsapiens.dbSNP.**20100427 (i.e. dbSNP Build 131),
>> SNPs are mapped to GRCh37 (UCSC hg19) instead of hg18.
>>
>
> I've made some improvements to the SNPlocs packages. The improved
> packages are in BioC 2.9 (current devel, soon to be released) and
> had their versions bumped to 0.99.6. They are:
>
>  SNPlocs.Hsapiens.dbSNP.**20090506: dbSNP Build 130, based on hg18
>  SNPlocs.Hsapiens.dbSNP.**20100427: dbSNP Build 131, based on hg19
>  SNPlocs.Hsapiens.dbSNP.**20101109: dbSNP Build 132, based on hg19
>  SNPlocs.Hsapiens.dbSNP.**20110815: dbSNP Build 134, based on hg19
>
> Only the source packages are available at the moment but they should
> be installable on Windows/Mac from R-2.14 with
>
>  biocLite(..., type="source").
>
> The data in those packages have not changed but are organized more
> efficiently. There is a new function rsidsToGRanges() to extract
> SNP information for a set of rs ids. Using rsidsToGRanges() is
> much more memory (1/10) and time efficient (40x) than using the
> code I provided above. See ?rsidsToGRanges for the details.
>
> Let me know if you have questions.
>
> Cheers,
>
> H.
>
>
>> Hope this helps,
>> H.
>>
>>
>>> Further, I find dbSNP batch queries a little more difficult to work
>>> with because they map to different versions of the hg18 like Celera,
>>> HumanRef, etc.Can anybody let me know a better option to get hg18 chr
>>> position with the most popular or confident version of dbSNP?
>>>
>>> Thanks in advance
>>>
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>>>
>>
>>
>>
>
> --
> Hervé Pagès
>
> Program in Computational Biology
> Division of Public Health Sciences
> Fred Hutchinson Cancer Research Center
> 1100 Fairview Ave. N, M1-B514
> P.O. Box 19024
> Seattle, WA 98109-1024
>
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>
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