Great, thanks! Your initial solution did work quite well actually, but it did take me some time to grok. I had to apply it again recently, and decided to take a second look (which is when I think I tweeted about it). In general, I do agree that it would be helpful if there were a reference for these types of tricks. I love GenomicRanges because with some playing around, anything is possible and surprisingly fast. But maybe a higher-level vignette covering efficiency tricks would be helpful? I think if intermediate to advanced learning material peeked under the hood of GenomicRanges a bit, readers might be able to build up their intuition. I find this is the best way to figure how why something may be slow and how to fix it. thanks again, Vince On Fri, Mar 28, 2014 at 11:42 PM, Michael Lawrence < lawrence.michael@gene.com> wrote: > Actually, just realized that 'a' would need to be a RangesList, so it is > more like: > > ## assuming 'a' is in chromosome order (which it probably is) > a$overlap.with.b <- unlist(viewSums(Views(coverage(reduce(b)), as(a, > "RangesList")))) > > It would be nice if we could perform Views aggregations with GRanges. One > possibility would just be view* shortcuts for GRanges, like: > a$overlap.with.b <- viewSums(coverage(reduce(b)), a) > > That gets around the need to represent a Views with GRanges. > > Without Views, you would need to find overlaps and aggregate conditional > on the query index factor, instead of range-based aggregation. This > approach is less natural in my opinion: > > hits <- findOverlaps(a, reduce(b)) > w <- width(ranges(hits, a, b)) > a$overlap.with.b <- sum(relist(w, as(hits, "List"))) > > > > > On Fri, Mar 28, 2014 at 8:24 PM, Michael Lawrence <michafla@gene.com>wrote: > >> So it seems like from twitter that you still haven't solved this. I'm >> pretty sure this is as simple as: >> >> a$overlap.with.b <- viewSums(Views(coverage(reduce(b)), a)) >> >> But maybe I'm not exactly understanding what you want. >> >> Michael >> >> >> >> On Mon, Jan 6, 2014 at 2:52 PM, Vince S. Buffalo <vsbuffalo@gmail.com>wrote: >> >>> Hi Bioconductor folks, >>> >>> I'm trying to create some GRanges summaries, but I think I may be missing >>> an obvious solution. I have fixed-width windows as a GRanges object, and >>> for each window/row I'd like to add a metadata column that indicates how >>> many base pairs of this window overlap features in another GRange object. >>> I'll need to add a few columns for different features in different >>> GRanges >>> objects. >>> >>> I've tried using the approach of findOverlaps, followed by ranges() to >>> extract range widths. This creates an error: "'query' must be a Ranges of >>> length equal to number of queries". I saw in the source >>> that pintersect(query[queryHits(x)], subject[subjectHits(x)]) works too >>> (and does without error). This returns the overlapping ranges, but it'd >>> take a load of data munging to get it into the format I'd like -- it seems >>> like I may be overlooking an easier solution. >>> >>> thanks, >>> Vince >>> >>> !> sessionInfo() >>> R version 3.0.2 (2013-09-25) >>> Platform: x86_64-apple-darwin13.0.1 (64-bit) >>> >>> locale: >>> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 >>> >>> attached base packages: >>> [1] parallel stats graphics grDevices utils datasets methods >>> [8] base >>> >>> other attached packages: >>> [1] ggplot2_0.9.3.1 rtracklayer_1.22.0 GenomicRanges_1.14.3 >>> [4] XVector_0.2.0 IRanges_1.20.6 BiocGenerics_0.8.0 >>> [7] ESSR_1.0.1 >>> >>> loaded via a namespace (and not attached): >>> [1] Biostrings_2.30.1 bitops_1.0-6 BSgenome_1.30.0 >>> colorspace_1.2-4 >>> [5] compiler_3.0.2 dichromat_2.0-0 digest_0.6.4 grid_3.0.2 >>> [9] gtable_0.1.2 labeling_0.2 MASS_7.3-29 >>> munsell_0.4.2 >>> [13] plyr_1.8 proto_0.3-10 RColorBrewer_1.0-5 >>> RCurl_1.95-4.1 >>> [17] reshape2_1.2.2 Rsamtools_1.14.2 scales_0.2.3 >>> stats4_3.0.2 >>> [21] stringr_0.6.2 tools_3.0.2 XML_3.98-1.1 >>> zlibbioc_1.8.0 >>> >>> -- >>> Vince Buffalo >>> Ross-Ibarra Lab www.rilab.org) >>> Plant Sciences, UC Davis >>> >>> [[alternative HTML version deleted]] >>> >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor@r-project.org >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >> >> > -- Vince Buffalo Ross-Ibarra Lab www.rilab.org) Plant Sciences, UC Davis [[alternative HTML version deleted]]