Yes poverlaps(). Or pcompare(), which should be even faster. But only if you are not afraid to go low-level. See ?rangeComparisonCodeToLetter for the meaning of the codes returned by pcompare().
H. On 1/29/20 08:01, Michael Lawrence via Bioc-devel wrote: > poverlaps()? > > On Wed, Jan 29, 2020 at 7:50 AM web working <webwork...@posteo.de> wrote: >> >> Hello, >> >> I have two big GRanges objects and want to search for an overlap of the >> first range of query with the first range of subject. Then take the >> second range of query and compare it with the second range of subject >> and so on. Here an example of my problem: >> >> # GRanges objects >> query <- GRanges(rep("chr1", 4), IRanges(c(1, 5, 9, 20), c(2, 6, 10, >> 22)), id=1:4) >> subject <- GRanges(rep("chr1",4), IRanges(c(3, 1, 1, 15), c(4, 2, 2, >> 21)), id=1:4) >> >> # The 2 overlaps at the first position should not be counted, because >> these ranges are at different rows. >> countOverlaps(query, subject) >> >> # Approach 1 (bad style. I have simplified it to understand) >> dat <- as.data.frame(findOverlaps(query, subject)) >> indexDat <- apply(dat, 1, function(x) x[1]==x[2]) >> indexBool <- dat[indexDat,1] >> out <- rep(FALSE, length(query)) >> out[indexBool] <- TRUE >> as.numeric(out) >> >> # Approach 2 (bad style and takes too long) >> out <- vector("numeric", 4) >> for(i in seq_along(query)) out[i] <- (overlapsAny(query[i], subject[i])) >> out >> >> # Approach 3 (wrong results) >> as.numeric(overlapsAny(query, subject)) >> as.numeric(overlapsAny(split(query, 1:4), split(subject, 1:4))) >> >> >> Maybe someone has an idea to speed this up? >> >> >> Best, >> >> Tobias >> >> _______________________________________________ >> Bioc-devel@r-project.org mailing list >> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.ethz.ch_mailman_listinfo_bioc-2Ddevel&d=DwICAg&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=FSrHBK59_OMc6EbEtcPhkTVO0cfDgSbQBGFOXWyHhjc&s=3tZpvRAw7T5dP21u32TRTf4lZ4QFLtmkouKR7TUlJws&e= > > > -- Hervé Pagès Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpa...@fredhutch.org Phone: (206) 667-5791 Fax: (206) 667-1319 _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel