I have a solution (actually a few) to this problem, but none are
computationally efficient enough to be useful. I'm hoping someone can
enlighten me to a better solution.
I have data frame of chromosome/position pairs (along with other data for the
location). For each pair I need to determine if it is with in a given data
frame of ranges. I need to keep only the pairs that are within any of the
ranges for further processing.
Example:
snps<-NULL
snps$CHR<-c("1","2","2","3","X")
snps$POS<-as.integer(c(295,640,670,100,1100))
snps$DAT<-seq(1:length(snps$CHR))
snps<-as.data.frame(snps, stringsAsFactors=FALSE)
snps
CHR POS DAT
1 1 295 1
2 2 640 2
3 2 670 3
4 3 100 4
5 X 1100 5
region<-NULL
region$CHR<-c("1","1","2","2","2","X")
region$START<-as.integer(c(10,210,430,650,810,1090))
region$STOP<-as.integer(c(100,350,630,675,850,1111))
region<-as.data.frame(region, stringsAsFactors=FALSE)
region
CHR START STOP
1 1 10 100
2 1 210 350
3 2 430 630
4 2 650 675
5 2 810 850
6 X 1090 1111
The result I need would look like
Res
CHR POS DAT
1 295 1
2 670 3
X 1100 5
I have a solution that works reasonably well on small sets, but my current data
set is ~100K snp entries, and my regions table has ~200K entries. I have ~1500
files to go through
I haven't found a good way to efficiently solve this problem. I've tried
various versions of mapply/lapply, for loops, etc which get the answer for
small sets but takes hours (per file) on my real data. Bioconductor seemed
like the obvious place to look, but my GoogleFu must not be that great. I
never found anything relevant.
Any ideas or points to the right direction would be greatly appreciated.
Brian Davis
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