What is the easiest method in 2017 to obtain build 37 positions for a batch of rsIDs? This site does not seem to support specific builds: https://www.ncbi.nlm.nih.gov/projects/SNP/dbSNP.cgi?list=rslist
The opposite question has been asked in here; go from coordinate to rsID.
I wouldn't mind Python based suggestions at all.
EDIT: I found a solution using the Entrez class of the Python module Biopython here: http://www.danielecook.com/getting_snp_dat/
It's a bit convoluted. I'll simplify it a bit and post the solution.
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by
Tommy Carstensen
$ mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D hg19 -e 'select chrom,chromStart,chromEnd,name from snp147 where name in ("rs371194064","rs779258992","rs26","rs25")'
+-------+------------+----------+-------------+
| chrom | chromStart | chromEnd | name |
+-------+------------+----------+-------------+
| chr7 | 11584141 | 11584142 | rs25 |
| chr7 | 11583470 | 11583471 | rs26 |
| chr1 | 10149 | 10150 | rs371194064 |
| chr1 | 10146 | 10147 | rs779258992 |
+-------+------------+----------+-------------+
If one wants to see all of the available columns, then do:
mysql --user=genome --host=genome-mysql.cse.ucsc.edu -A -D hg19 -e 'show columns from snp147'
One of the easiest ways is to use dbSNP database pre-formatted in annovar format from here (v147) http://www.openbioinformatics.org/annovar/download/hg19_avsnp147.txt.gz
It looks like this:
1 10019 10020 TA T rs775809821
1 10020 10020 A - rs775809821
1 10055 10055 - A rs768019142
1 10055 10055 T TA rs768019142
1 10108 10108 C T rs62651026
1 10109 10109 A T rs376007522
Then it's just a matter of picking and associating the rsID from this table. Unix join or merge() in R can do that easily.
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Santosh Anand
I guess you are actually right about that Santosh. Thanks for your suggestion. I'll go for it despite the file being nearly 2GB in size. I'm just surprised Biopython doesn't have some simple function for doing it.
@Santosh , this link seems great but doesn't work anymore. Do you know where one can get that table now? Thanks.
Check it again, please. It does work for me.
You're right, it works. Who knows what I was doing that day... Thanks!
Thanks Emily! Currently hundreds of rsIDs and probably never more than tens of thousands of rsIDs. The solution from Pierre is fast for hundreds of rsIDs. I know how to do it in Python, but that's quite a few lines of code.
Alternative for R.
library("biomaRt")
snp_mart = useMart(biomart = "ENSEMBL_MART_SNP",
host = "grch37.ensembl.org",
path = "/biomart/martservice",
dataset = "hsapiens_snp")
# list of variables (attributes) that can be retrieved
# listAttributes(mart = snp_mart)
# list of keywords (filters) that you can merge on
# listFilters(mart = snp_mart)
out <- getBM(attributes = c('refsnp_id', 'chr_name', 'chrom_start', 'allele'),
filters = c('snp_filter'),
values = list(df$rsid),
mart = snp_mart)
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