I have a data.table (A) that is over 100,000 rows long. There are 3 columns.
chrom start end
1: chr1 6484847 6484896
2: chr1 6484896 6484945
3: chr1 6484945 6484994
4: chr1 6484994 6485043
5: chr1 6485043 6485092
---
183569: chrX 106893605 106893654
183570: chrX 106893654 106893703
183571: chrX 106893703 106893752
183572: chrX 106893752 106893801
183573: chrX 106893801 106894256
chrom start end gene
1: chr1 6484847 6521004 ESPN
2: chr1 41249683 41306124 KCNQ4
3: chr1 55464616 55474465 BSND
42: chrX 82763268 82764775 POU3F4
43: chrX 100600643 100603957 TIMM8A
44: chrX 106871653 106894256 PRPS1
chrom start end gene
1: chr1 6484847 6484896 ESPN
2: chr1 6484896 6484945 ESPN
3: chr1 6484945 6484994 ESPN
4: chr1 6484994 6485043 ESPN
5: chr1 6485043 6485092 ESPN
---
183569: chrX 106893605 106893654 TIMM8A
183570: chrX 106893654 106893703 TIMM8A
183571: chrX 106893703 106893752 TIMM8A
183572: chrX 106893752 106893801 TIMM8A
183573: chrX 106893801 106894256 TIMM8A
While it's certainly possible to do this in base R (or potentially using data.table
), I would highly recommend using GenomicRanges
; it's a very powerful and flexible R/Bioconductor library that's been designed for these kind of tasks.
Here is an example using GenomicRanges::findOverlaps
:
# Sample data
df1 <- read.table(text =
"chrom start end
chr1 6484847 6484896
chr1 6484896 6484945
chr1 6484945 6484994
chr1 6484994 6485043
chr1 6485043 6485092", sep = "", header = T, stringsAsFactors = F);
df2 <- read.table(text =
"chrom start end gene
chr1 6484847 6521004 ESPN
chr1 41249683 41306124 KCNQ4
chr1 55464616 55474465 BSND
chrX 82763268 82764775 POU3F4
chrX 100600643 100603957 TIMM8A
chrX 106871653 106894256 PRPS1", sep = "", header = TRUE, stringsAsFactors = F);
# Convert to GRanges objects
gr1 <- with(df1, GRanges(chrom, IRanges(start = start, end = end)));
gr2 <- with(df2, GRanges(chrom, IRanges(start = start, end = end), gene = gene));
# Find features from gr1 that overlap with gr2
m <- findOverlaps(gr1, gr2);
# Add gene annotation as metadata to gr1
mcols(gr1)$gene[queryHits(m)] <- mcols(gr2)$gene[subjectHits(m)];
gr1;
#GRanges object with 5 ranges and 1 metadata column:
# seqnames ranges strand | gene
# <Rle> <IRanges> <Rle> | <character>
# [1] chr1 [6484847, 6484896] * | ESPN
# [2] chr1 [6484896, 6484945] * | ESPN
# [3] chr1 [6484945, 6484994] * | ESPN
# [4] chr1 [6484994, 6485043] * | ESPN
# [5] chr1 [6485043, 6485092] * | ESPN
# -------
# seqinfo: 1 sequence from an unspecified genome; no seqlengths