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I am using library(biomaRt) in R to annotate SNP rsid. It takes too much time for only 1000 SNPs....... I would like to know how I can run this code faster.

 coords<-data
 coords$chr_name<-coords$chromosome
 coords$start<-coords$position
 coords$end<-coords$position
 coords<-coords%>%dplyr::select(chr_name,start,end)
 mart=useMart(biomart="ENSEMBL_MART_SNP", host="grch37.ensembl.org",     
 path="/biomart/martservice", dataset="hsapiens_snp")
 results=data.frame(matrix(ncol=4,nrow=0))
 for (i in seq (1,nrow(coords)))
{
ens=getBM(attributes = c('refsnp_id','allele','chrom_start','chrom_strand'),     
filters = c('chr_name','start','end'), values = as.list(coords[i,]), mart = mart)
results=rbind(results,ens)}

I am using the following code, but still not working......

coords$newposition<-paste0(coords$chromosome,":",coords$position)
coords$chromosomal_region<-paste0(coords$newposition,":",coords$position)
coords<-coords$chromosomal_region
res<-getBM(attributes = c('refsnp_id','allele','chrom_start','chrom_strand'), 
   filters = 'chromosomal_region', 
   values = coords, 
   mart = mart)
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    $\begingroup$ I am also facing the same issue. I have 5600 SNPs and even after vectorization, I am facing the same timeout problem even for 500 SNPs. $\endgroup$
    – Jyoti Sharma
    Jan 13 at 7:51

1 Answer 1

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Don't run getBM 1000 times. It can handle whole vectors, and get you all your results at once.

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  • $\begingroup$ Sorry, could give me some example codes? $\endgroup$
    – user224050
    Oct 9, 2020 at 22:30
  • $\begingroup$ vectorising the function is a good idea and would speed up the process. It would be nice if @swbarnes2 gave a less terse answer with e.g some example code on how to achieve it. $\endgroup$
    – user438383
    Oct 10, 2020 at 13:15

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