Thank you Stuart and Michael for your feedback. Stuart, in response to your request for more context regarding my use case, I have updated my recent BioC support post<https://support.bioconductor.org/p/125623/>, now providing all use-case details.
Michael, I didn't selfmatch yet, but Stuart's reply seems to suggest that it would not get the data.table performance (which is literally instantaneous). As a general question, do you think it would be useful to add a data.table-based split-apply-combine functionality to plyranges (such that end user operations remain on GRanges-only)? I wouldn't mind writing a function to do that (in github), but first need your feedback as to whether you think that would be useful :-) Aditya ________________________________ From: Stuart Lee [le...@wehi.edu.au] Sent: Thursday, October 17, 2019 3:01 AM To: Michael Lawrence Cc: Bhagwat, Aditya; bioc-devel@r-project.org Subject: Re: plyranges group_by Currently, the way grouping indices are generated is pretty slow if you�re doing stuff rowwise. Michael�s suggestion for using selfmatch should speed things up a bit. What are you planning to do after grouping? I�ve found there�s usually to do stuff without rowwise grouping but really depends on what you�re after. Re your other issue would you mind putting it on as a GitHub issue. � Stuart Lee Visiting PhD Student - Ritchie Lab On 16 Oct 2019, at 22:54, Michael Lawrence <lawrence.mich...@gene.com<mailto:lawrence.mich...@gene.com>> wrote: Just a note that in this particular case, selfmatch(annotatedsrf) would be a fast way to generate a grouping vector, like plyranges::group_by(annotatedsrf, selfmatch(annotatedsrf)). Michael On Wed, Oct 16, 2019 at 2:48 AM Bhagwat, Aditya <aditya.bhag...@mpi-bn.mpg.de<mailto:aditya.bhag...@mpi-bn.mpg.de>> wrote: Hi Stuart, Michael, Your plyranges package is really cool - now I am using it for left joining GRanges (I am facing a minor issue there<https://support.bioconductor.org/p/125623/>, but that is not the topic of this email - I have been asked by Lori not to double-post :-)). This email is about the plyranges functionality for grouping GRanges. That is cool, but I found it to be not so performant for large numbers of ranges. My R session hangs when I do: bedfile <- paste0('https://gitlab.gwdg.de/loosolab/software/multicrispr/wikis', '/uploads/a51e98516c1e6b71441f5b5a5f741fa1/SRF.bed') srfranges <- rtracklayer::import.bed(bedfile, genome = 'mm10') txdb <- TxDb.Mmusculus.UCSC.mm10.ensGene::TxDb.Mmusculus.UCSC.mm10.ensGene generanges <- GenomicFeatures::genes(txdb) annotatedsrf <- plyranges::join_overlap_left(srfranges, generanges) plyranges::group_by(annotatedsrf, seqnames, start, end, strand) For my purposes, I worked around it by performing a groupby in data.table: data.table::as.data.table(annotatedsrf)[ !is.na<http://is.na/>(gene_id), gene_id := paste0(gene_id, collapse = ';'), by = c('seqnames', 'start', 'end', 'strand')) And was wondering, in general, whether it would be useful to have a data.table-based backend for plyranges::groupby() And, whether all of this is actually a on-issue due to my improper use of plyranges::group_by properly. Thank you for feebdack :-) Aditya -- Michael Lawrence Scientist, Bioinformatics and Computational Biology Genentech, A Member of the Roche Group Office +1 (650) 225-7760 micha...@gene.com<mailto:micha...@gene.com> Join Genentech on LinkedIn | Twitter | Facebook | Instagram | YouTube _______________________________________________ The information in this email is confidential and intend...{{dropped:15}}
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