Of course. It's always a one-liner. Thanks very much! :)
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kamaitachi •
How do I summarize a GRanges data frame into "one complete RLE"?
I have a GRanges data frame corresponding to a mappability track that looks like this:
> m
GRanges with 31194271 ranges and 1 metadata column:
seqnames ranges strand | mappable
<Rle> <IRanges> <Rle> | <Rle>
[1] 4 [5981, 5985] * | FALSE
[2] 4 [5986, 5990] * | FALSE
[3] 4 [5991, 5995] * | FALSE
[4] 4 [5996, 6000] * | FALSE
[5] 4 [6001, 6005] * | FALSE
... ... ... ... ... ...
[31194267] dmel_mitochondrion_genome [19496, 19500] * | FALSE
[31194268] dmel_mitochondrion_genome [19501, 19505] * | FALSE
[31194269] dmel_mitochondrion_genome [19506, 19510] * | FALSE
[31194270] dmel_mitochondrion_genome [19511, 19515] * | FALSE
[31194271] dmel_mitochondrion_genome [19516, 19517] * | FALSE
How can I summarize the ranges so that, for example, the region of chromosome 4, Ranges 5981-6005 get summarized into one line of FALSEs?
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Ram
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kamaitachi •
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kamaitachi •
1 answer
reduce(m)
Edit: I guess you want the extra columns too. In that case it's a bit more complicated.
m2 <- reduce(m) IDX <- findOverlaps(m, m2) IDX2 <- IDX[which(!duplicated(subjectHits(IDX))),] #Just assign things once mcols(m2)$mappable[subjectHits(IDX2)] <- mcols(m)$mappable[queryHits(IDX2)]
or something quite close to that.
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Devon Ryan
Note the update! I'd forgotten about the metadata columns, which you want to keep. There's no inbuilt way to get reduce() to keep those, so I just assign the first value of the original object. One could think of more complicated ways to do that, likely by splitting the output by subjectHits() and then applying a function.
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