Hello Martin, Jonathan and everybody,

I was unaware of the existence of scanBam and read.bed().

I'm glad I brought up the issue. Thank you.

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 Thu, Mar 10, 2011 at 9:08 AM, Jonathan Cairns
<[email protected]> wrote:
> FWIW, If you need only the chr, start, end and strand information from a BED 
> file, the function read.bed() in the BayesPeak package does this. Moreover it 
> is usually around twice as fast as import() because it ignores the rest of 
> the columns. However, it cannot yet handle the compressed .bed.gz format.
>
> Perhaps this would be a useful option in import.bed()? From my experience, 
> use of BED files is not that uncommon for ChIP-seq reads.
>
> Jonathan
> ________________________________________
> From: [email protected] 
> [[email protected]] On Behalf Of Ivan Gregoretti 
> [[email protected]]
> Sent: 09 March 2011 16:18
> To: Michael Lawrence
> Cc: [email protected]
> Subject: Re: [Bioc-sig-seq] BED file parser
>
> 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
> <[email protected]> wrote:
>>
>>
>> On Wed, Mar 9, 2011 at 7:33 AM, Ivan Gregoretti <[email protected]> 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
>>> <[email protected]> wrote:
>>> >
>>> >
>>> > On Wed, Mar 9, 2011 at 6:41 AM, Ivan Gregoretti <[email protected]>
>>> > 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
>>> >> <[email protected]> wrote:
>>> >> > 2011/3/8 Thiago Yukio Kikuchi Oliveira <[email protected]>:
>>> >> >> 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: [email protected]
>>> >> >>   /=)            [email protected]
>>> >> >> (=/
>>> >> >>   /    Bioinformatic Team - BiT: http://lgmb.fmrp.usp.br
>>> >> >> (=\   Hemocentro de Ribeirão Preto: http://pegasus.fmrp.usp.br
>>> >> >>   \=)
>>> >> >>    /
>>> >> >> -----------------------------------------------------------------
>>> >> >>
>>> >> >> _______________________________________________
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>>> >> >> [email protected]
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>>> >> >>
>>> >> >
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>>> >>
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>>
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