I use BED because it uses less memory. BAM format contains the read names, the sequences, the quality string and more information. I do not need that. I only need chromosome name, start, end, and strand.
So, for almost all my analyses, I start by converting my .bam to a minimalistic .bed.gz outside R and then from R I load my tags into a GRanges with import(). As simple as that. Ivan Ivan Gregoretti, PhD National Institute of Diabetes and Digestive and Kidney Diseases National Institutes of Health 5 Memorial Dr, Building 5, Room 205. Bethesda, MD 20892. USA. Phone: 1-301-496-1016 and 1-301-496-1592 Fax: 1-301-496-9878 On Wed, Mar 9, 2011 at 10:51 AM, Michael Lawrence <lawrence.mich...@gene.com> wrote: > > > On Wed, Mar 9, 2011 at 7:33 AM, Ivan Gregoretti <ivang...@gmail.com> wrote: >> >> I find simple BED files to be slow to import. I only use BED without >> track headers. The data is derived mostly from *-seq so we are talking >> about multiple million lines per file. >> >> The problem as I understand it is that the function reads one row at a >> time. It could be much faster if it read, say, 1000 rows at a time. >> > > I hope it's not reading one row at a time. It just calls read.table(), in a > fairly efficient way, with colClasses specified, etc. Why do you have high > throughput sequencing results in BED files? BED is really for genes. Most > other things fit into BAM, bedGraph (which uses the same basic parser > though), WIG, etc. > >> >> I never get errors. There are no bugs to fix. It's just very slow for >> the real world of high throughput sequencing. That's all. >> >> Thanks, >> >> Ivan >> >> >> Ivan Gregoretti, PhD >> National Institute of Diabetes and Digestive and Kidney Diseases >> National Institutes of Health >> 5 Memorial Dr, Building 5, Room 205. >> Bethesda, MD 20892. USA. >> Phone: 1-301-496-1016 and 1-301-496-1592 >> Fax: 1-301-496-9878 >> >> >> >> On Wed, Mar 9, 2011 at 10:21 AM, Michael Lawrence >> <lawrence.mich...@gene.com> wrote: >> > >> > >> > On Wed, Mar 9, 2011 at 6:41 AM, Ivan Gregoretti <ivang...@gmail.com> >> > wrote: >> >> >> >> Just to expand a little bit Vincent's response. >> >> >> >> If you happen to be handling very large BED files, you probably keep >> >> them compressed. The good news is that even in that case, you can load >> >> them: >> >> >> >> lit = import("~/lit.bed.gz"."bed") >> >> >> >> There is still the long-standing issue of how slow the import() >> >> function is but I am still hopeful. >> >> >> > >> > This is the first I've heard of this. What sort of files are slow? Do >> > they >> > have a track line? The parsing gets complicated when there are track >> > lines >> > and multiple tracks in a file. BED is a complex format with many >> > variants. >> > >> >> >> >> Ivan >> >> >> >> Ivan Gregoretti, PhD >> >> National Institute of Diabetes and Digestive and Kidney Diseases >> >> National Institutes of Health >> >> 5 Memorial Dr, Building 5, Room 205. >> >> Bethesda, MD 20892. USA. >> >> Phone: 1-301-496-1016 and 1-301-496-1592 >> >> Fax: 1-301-496-9878 >> >> >> >> >> >> >> >> On Tue, Mar 8, 2011 at 9:26 PM, Vincent Carey >> >> <st...@channing.harvard.edu> wrote: >> >> > 2011/3/8 Thiago Yukio Kikuchi Oliveira <strat...@gmail.com>: >> >> >> Hi, >> >> >> >> >> >> Is there a BED file parser for R? >> >> > >> >> > I suppose it depends on what you mean by "parser". import() from the >> >> > rtracklayer package imports BED and constructs and populates a >> >> > RangedData object with the contents. Here we look at a small bed >> >> > file >> >> > in text, >> >> > start R, load rtracklayer, import the data, show the result, and show >> >> > the resources used. >> >> > >> >> > bash-3.2$ head ~/junc716_20.bed >> >> > chr20 55658 64827 JUNC00000001 14 + 55658 64827 >> >> > 255,0,0 2 27,25 0,9144 >> >> > chr20 55662 64821 JUNC00000002 2 - 55662 64821 >> >> > 255,0,0 2 34,8 0,9151 >> >> > chr20 135774 147029 JUNC00000003 1 - 135774 >> >> > 147029 >> >> > 255,0,0 2 8,29 0,11226 >> >> > chr20 167951 172361 JUNC00000004 1 + 167951 >> >> > 172361 >> >> > 255,0,0 2 29,8 0,4402 >> >> > chr20 189824 192113 JUNC00000005 3 + 189824 >> >> > 192113 >> >> > 255,0,0 2 33,9 0,2280 >> >> > chr20 189829 192113 JUNC00000006 3 + 189829 >> >> > 192113 >> >> > 255,0,0 2 32,9 0,2275 >> >> > chr20 193930 199576 JUNC00000007 4 - 193930 >> >> > 199576 >> >> > 255,0,0 2 28,11 0,5635 >> >> > chr20 207050 207846 JUNC00000008 2 - 207050 >> >> > 207846 >> >> > 255,0,0 2 20,34 0,762 >> >> > chr20 218306 218925 JUNC00000009 1 - 218306 >> >> > 218925 >> >> > 255,0,0 2 11,26 0,593 >> >> > chr20 221160 225070 JUNC00000010 25 - 221160 >> >> > 225070 >> >> > 255,0,0 2 29,9 0,3901 >> >> > bash-3.2$ head ~/junc716_20.bed > ~/lit.bed >> >> > bash-3.2$ R213 --vanilla --quiet >> >> >> library(rtracklayer) >> >> > Loading required package: RCurl >> >> > Loading required package: bitops >> >> >> lit = import("~/lit.bed") >> >> >> lit >> >> > RangedData with 10 rows and 9 value columns across 1 space >> >> > space ranges | name score strand >> >> > thickStart >> >> > <character> <IRanges> | <character> <numeric> <character> >> >> > <integer> >> >> > 1 chr20 [ 55659, 64827] | JUNC00000001 14 + >> >> > 55658 >> >> > 2 chr20 [ 55663, 64821] | JUNC00000002 2 - >> >> > 55662 >> >> > 3 chr20 [135775, 147029] | JUNC00000003 1 - >> >> > 135774 >> >> > 4 chr20 [167952, 172361] | JUNC00000004 1 + >> >> > 167951 >> >> > 5 chr20 [189825, 192113] | JUNC00000005 3 + >> >> > 189824 >> >> > 6 chr20 [189830, 192113] | JUNC00000006 3 + >> >> > 189829 >> >> > 7 chr20 [193931, 199576] | JUNC00000007 4 - >> >> > 193930 >> >> > 8 chr20 [207051, 207846] | JUNC00000008 2 - >> >> > 207050 >> >> > 9 chr20 [218307, 218925] | JUNC00000009 1 - >> >> > 218306 >> >> > 10 chr20 [221161, 225070] | JUNC00000010 25 - >> >> > 221160 >> >> > thickEnd itemRgb blockCount blockSizes blockStarts >> >> > <integer> <character> <integer> <character> <character> >> >> > 1 64827 #FF0000 2 27,25 0,9144 >> >> > 2 64821 #FF0000 2 34,8 0,9151 >> >> > 3 147029 #FF0000 2 8,29 0,11226 >> >> > 4 172361 #FF0000 2 29,8 0,4402 >> >> > 5 192113 #FF0000 2 33,9 0,2280 >> >> > 6 192113 #FF0000 2 32,9 0,2275 >> >> > 7 199576 #FF0000 2 28,11 0,5635 >> >> > 8 207846 #FF0000 2 20,34 0,762 >> >> > 9 218925 #FF0000 2 11,26 0,593 >> >> > 10 225070 #FF0000 2 29,9 0,3901 >> >> > >> >> >> sessionInfo() >> >> > R version 2.13.0 Under development (unstable) (2011-03-01 r54628) >> >> > Platform: x86_64-apple-darwin10.4.0/x86_64 (64-bit) >> >> > >> >> > locale: >> >> > [1] C >> >> > >> >> > attached base packages: >> >> > [1] stats graphics grDevices utils datasets methods base >> >> > >> >> > other attached packages: >> >> > [1] rtracklayer_1.11.11 RCurl_1.5-0 bitops_1.0-4.1 >> >> > >> >> > loaded via a namespace (and not attached): >> >> > [1] BSgenome_1.19.4 Biobase_2.11.9 Biostrings_2.19.15 >> >> > [4] GenomicRanges_1.3.23 IRanges_1.9.25 Matrix_0.999375-47 >> >> > [7] XML_3.2-0 grid_2.13.0 lattice_0.19-17 >> >> > >> >> > >> >> >> >> >> >> >> >> >> Thanks >> >> >> >> >> >> / Thiago Yukio Kikuchi Oliveira >> >> >> (=\ >> >> >> \=) Faculdade de Medicina de Ribeirão Preto >> >> >> / Laboratório de Genética Molecular e Bioinformática >> >> >> /=) >> >> >> ----------------------------------------------------------------- >> >> >> (=/ Centro de Terapia Celular/CEPID/FAPESP - Hemocentro de Rib. >> >> >> Preto >> >> >> / Rua Tenente Catão Roxo, 2501 CEP 14151-140 >> >> >> (=\ Ribeirão Preto - São Paulo >> >> >> \=) Fone: 55 16 2101-9300 Ramal: 9603 >> >> >> / E-mail: stra...@lgmb.fmrp.usp.br >> >> >> /=) strat...@gmail.com >> >> >> (=/ >> >> >> / Bioinformatic Team - BiT: http://lgmb.fmrp.usp.br >> >> >> (=\ Hemocentro de Ribeirão Preto: http://pegasus.fmrp.usp.br >> >> >> \=) >> >> >> / >> >> >> ----------------------------------------------------------------- >> >> >> >> >> >> _______________________________________________ >> >> >> Bioc-sig-sequencing mailing list >> >> >> Bioc-sig-sequencing@r-project.org >> >> >> https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing >> >> >> >> >> > >> >> > _______________________________________________ >> >> > Bioc-sig-sequencing mailing list >> >> > Bioc-sig-sequencing@r-project.org >> >> > https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing >> >> > >> >> >> >> _______________________________________________ >> >> Bioc-sig-sequencing mailing list >> >> Bioc-sig-sequencing@r-project.org >> >> https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing >> > >> > > > _______________________________________________ Bioc-sig-sequencing mailing list Bioc-sig-sequencing@r-project.org https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing