[Bioc-sig-seq] understanding memory size of AlignedRead objects
Hervé Pagès
hpages at fhcrc.org
Fri May 13 12:22:41 CEST 2011
Hi Janet,
I've committed a few changes to IRanges/Biostrings/ShortRead that
should address the problem you are experiencing with compact():
library(ShortRead)
dirPath <- "Data/C1-36Firecrest/Bustard/GERALD"
bigaln <- readAligned(dirPath, "big_s_2_export.txt", "SolexaExport")
length(bigaln) # 16384000
object.size(bigaln) # 2457626736 bytes
## Size overhead for any AlignedRead object:
emptyaln <- bigaln[FALSE]
ALNovh <- object.size(emptyaln) # 20736 bytes
## Bytes per read:
(object.size(bigaln) - ALNovh) / length(bigaln) # 150 bytes
## Take the first 10000 elts:
first10000 <- bigaln[1:10000]
first10000_compact <- compact(first10000)
## Bytes per read:
(object.size(first10000_compact) - ALNovh) / 10000 # 150 bytes
Make sure you have IRanges >= 1.10.2, Biostrings >= 2.20.1 and
ShortRead >= 1.10.2 (should become available in release on
Friday around 11am Seattle time).
Cheers,
H.
> sessionInfo()
R version 2.13.0 (2011-04-13)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
[1] LC_CTYPE=en_CA.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_CA.UTF-8 LC_COLLATE=en_CA.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_CA.UTF-8
[7] LC_PAPER=en_CA.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ShortRead_1.10.2 Rsamtools_1.4.1 lattice_0.19-26
[4] Biostrings_2.20.1 GenomicRanges_1.4.3 IRanges_1.10.3
loaded via a namespace (and not attached):
[1] Biobase_2.12.1 grid_2.13.0 hwriter_1.3
On 11-05-10 05:16 PM, Janet Young wrote:
> Hi again,
>
> I've been looking into this question a bit more, now using compact(). Things seemed to go well with the example dataset provided with ShortRead (as far as I can tell). But when I use our own much larger dataset the compaction factor is not very good (my small object is the first 100 reads, the full set is ~18 million reads, but the small object is 40% the size in memory of the full object). I think it looks like quality and sreads haven't really been compacted nearly as much as I would expect. The code is below.
>
> Martin - if you would like access to this dataset I can email you about that privately, but I'm guessing the same would happen with any big dataset?
>
> Janet
>
>
>
> library(ShortRead)
>
> ########## a big dataset (our data)
>
> read2Dir<- "solexa/110317_SN367_0148_A81NVUABXX/Data/Intensities/BaseCalls/GERALD_24-03-2011_solexa.2"
>
> my_reads<- readAligned(read2Dir, pattern="s_1_export.txt", type="SolexaExport")
> my_reads_verysmall<- my_reads[1:100]
> my_reads_verysmall_compact<- compact(my_reads[1:100])
>
> length(my_reads)
> # [1] 17894091
> length(my_reads_verysmall)
> # [1] 100
> length(my_reads_verysmall_compact)
> # [1] 100
>
> object.size(my_reads)
> # 3190125528 bytes
> object.size(my_reads_verysmall)
> # 1753653496 bytes
> object.size(my_reads_verysmall_compact)
> # 1253663384 bytes
>
> as.numeric(object.size(my_reads_verysmall)) / as.numeric(object.size(my_reads))
> # [1] 0.549713
>
> as.numeric(object.size(my_reads_verysmall_compact)) / as.numeric(object.size(my_reads))
> # [1] 0.3929825
>
> ##### where is most of that memory?
> object.size(position(my_reads_verysmall_compact))
> # 440 bytes
> object.size(chromosome(my_reads_verysmall_compact))
> # 3040 bytes
> object.size(sread(my_reads_verysmall_compact))
> # 626820976 bytes
> object.size(quality(my_reads_verysmall_compact))
> # 626821568 bytes
>
> myDNA2<- DNAStringSet(as.character(sread(my_reads_verysmall_compact)))
> object.size(myDNA2)
> # 9944 bytes
>
>
> ###### and ShortRead's example dataset, 1000 reads
>
> exptPath<- system.file("extdata", package = "ShortRead")
> sp<- SolexaPath(exptPath)
> aln<- readAligned(sp, "s_2_export.txt")
>
> aln ## aln has 1000 reads
> aln_small<- aln[1:2] ### aln 2 has 2 reads
> aln_small_compact<- compact(aln[1:2])
>
> object.size(aln)
> # 175968 bytes
> object.size(aln_small)
> # 91488 bytes
> object.size(aln_small_compact)
> # 21744 bytes
>
> as.numeric(object.size(aln_small)) / as.numeric(object.size(aln))
> # [1] 0.5199127
>
> as.numeric(object.size(aln_small_compact)) / as.numeric(object.size(aln))
> # [1] 0.1235679
>
> myDNA<- DNAStringSet( as.character(sread(aln_small_compact)) )
> identical(myDNA,sread(aln_small_compact))
> [1] TRUE
>
> aln_medium_compact<- compact(aln[1:300])
> myDNA_medium<- DNAStringSet( as.character(sread(aln_medium_compact)) )
> identical(myDNA,sread(aln_medium_compact))
> # [1] FALSE
>
> aln_10_compact<- compact(aln[1:10])
> myDNA_10<- DNAStringSet( as.character(sread(aln_10_compact)) )
> identical(myDNA,sread(aln_10_compact))
> # [1] FALSE
>
> as.numeric(object.size(aln_10_compact)) / as.numeric(object.size(aln))
> # [1] 0.1317512
>
> #########
>
>
> sessionInfo()
>
> R version 2.13.0 (2011-04-13)
> Platform: x86_64-unknown-linux-gnu (64-bit)
>
> locale:
> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
> [5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
> [9] LC_ADDRESS=C LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] ShortRead_1.10.0 Rsamtools_1.4.0 lattice_0.19-23
> [4] Biostrings_2.20.0 GenomicRanges_1.4.0 IRanges_1.10.0
>
> loaded via a namespace (and not attached):
> [1] Biobase_2.12.0 grid_2.13.0 hwriter_1.3
>
>
>
>
> On May 10, 2011, at 4:25 PM, Martin Morgan wrote:
>
>> On 05/10/2011 02:47 PM, Janet Young wrote:
>>> Hi, (probably hello to you, Martin)
>>
>> Hi (or is that hello?) Janet --
>>
>>> I'm looking at some Illumina seq data, and trying to be more rigorous
>>> than I have been in the past about memory usage and tidying up unused
>>> variables. I'm a little mystified by something - I wonder if you can
>>> help me understand?
>>>
>>> I'm starting with a big AlignedRead object (one full lane of seq
>>> data) and then I've been using [] on AlignedRead objects to take
>>> various subsets of the data (and then looking at quality scores, map
>>> positions, etc). I'm also taking some very small subsets (e.g. just
>>> the first 100 reads) to test and optimize some functions I'm
>>> writing.
>>>
>>> My confusion comes because even though I'm cutting down the number of
>>> seq reads by a lot (e.g. from 18 million to just 100 reads), the new
>>> AlignedRead object still takes up a lot of memory.
>>
>> XStringSet (including DNAStringSet and BStringSet, which are used to hold AlignedRead sequence and quality information) are actually 'views' (start and end coordinates) on an underlying XString; when you subset a DNAStringSet, you subset the view but not the underlying DNAString. This might sound bad, but actually you have just one instance of the DNAString, and two light-weight views (the full view, and the subset view). If you're done with the full DNAString, you can force it to be compacated with compact(), e.g., after your first example
>>
>>> object.size(s1)
>> 50840 bytes
>>> object.size(s1[1:10]) # mostly smaller 'view'
>> 38984 bytes
>>> object.size(s1[1]) # a little smaller 'view', same big DNAString
>> 38864 bytes
>>> object.size(compact(s1[1]))
>> 3912 bytes
>>
>> or
>>
>>> object.size(aln)
>> 175968 bytes
>>> object.size(aln[1])
>> 91488 bytes
>>> object.size(compact(aln[1]))
>> 21584 bytes
>>
>> (I think Herve is working on your weighted coverage question)
>>
>> Martin
>>
>>>
>>> Two examples are given below - in both cases the small object takes
>>> about half as much memory as the original, even though the number of
>>> reads is now very much smaller.
>>>
>>> Do you have any suggestions as to how I might reduce the memory
>>> footprint of the subsetted AlignedRead object? Is this an expected
>>> behavior?
>>>
>>> thanks very much,
>>>
>>> Janet
>>>
>>>
>>> library(ShortRead)
>>>
>>> exptPath<- system.file("extdata", package = "ShortRead") sp<-
>>> SolexaPath(exptPath) aln<- readAligned(sp, "s_2_export.txt")
>>>
>>> aln ## aln has 1000 reads aln_small<- aln[1:2] ### aln 2 has 2
>>> reads
>>>
>>> object.size(aln) # 165156 bytes object.size(aln_small) # 82220 bytes
>>>
>>> as.numeric(object.size(aln_small)) / as.numeric(object.size(aln))
>>> #### [1] 0.4978324
>>>
>>> read2Dir<-
>>> "data/solexa/110317_SN367_0148_A81NVUABXX/Data/Intensities/BaseCalls/GERALD_24-03-2011_solexa.2"
>>>
>>>
>> my_reads<- readAligned(read2Dir, pattern="s_1_export.txt", type="SolexaExport")
>>> my_reads_verysmall<- my_reads[1:100]
>>>
>>> length(my_reads) # [1] 17894091 length(my_reads_verysmall) # [1] 100
>>>
>>> object.size(my_reads) # 3190125528 bytes
>>> object.size(my_reads_verysmall) # 1753653496 bytes
>>>
>>> as.numeric(object.size(my_reads_verysmall)) /
>>> as.numeric(object.size(my_reads)) # [1] 0.549713
>>>
>>>
>>>
>>> sessionInfo()
>>>
>>> R version 2.13.0 (2011-04-13) Platform: i386-apple-darwin9.8.0/i386
>>> (32-bit)
>>>
>>> locale: [1] en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>>>
>>> attached base packages: [1] stats graphics grDevices utils
>>> datasets methods base
>>>
>>> other attached packages: [1] ShortRead_1.10.0 Rsamtools_1.4.1
>>> lattice_0.19-26 Biostrings_2.20.0 [5] GenomicRanges_1.4.3
>>> IRanges_1.10.0
>>>
>>> loaded via a namespace (and not attached): [1] Biobase_2.12.1
>>> grid_2.13.0 hwriter_1.3
>>>
>>> _______________________________________________ Bioc-sig-sequencing
>>> mailing list Bioc-sig-sequencing at r-project.org
>>> https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
>>
>>
>> --
>> Computational Biology
>> Fred Hutchinson Cancer Research Center
>> 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109
>>
>> Location: M1-B861
>> Telephone: 206 667-2793
>
> _______________________________________________
> Bioc-sig-sequencing mailing list
> Bioc-sig-sequencing at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
--
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: hpages at fhcrc.org
Phone: (206) 667-5791
Fax: (206) 667-1319
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