Hi SangChul,

Can you attach your sessionInfo()? I will take a look into this issue.

best,
Vince

On Tue, Jun 5, 2012 at 12:01 PM, Sang Chul Choi <schoi@cornell.edu> wrote:

> I have tried to tunn off the option when reading sequences of variable
> lengths in a gzipped FASTQ file (2GB) using readSeqFile. The computer has
> 16 GB memory, and it used up all of the memory, leaving R in "Dead" or not
> running any more.  Is there a way of sidestepping this problem?
>
> Thank you,
>
> SangChul
>
> On Jun 1, 2012, at 4:55 PM, Vince Buffalo wrote:
>
> > Hi SangChul,
> >
> > By default readSeqFile hashes a proportion of the reads to check against
> many being non-unique. Specify hash=FALSE to turn this off and your memory
> usage will decrease.
> >
> > Best,
> > Vince
> >
> > Sent from my iPhone
> >
> > On Jun 1, 2012, at 1:23 PM, Sang Chul Choi <schoi@cornell.edu> wrote:
> >
> >> Hi,
> >>
> >> I am using qrqc to plot base quality of a short read fastq file. When
> the FASTQ file has short reads of the same length, the readSeqFile could
> read in the FASTQ file (25 millions of 100bp reads) with a couple of GB of
> memory. I trimmed 3' end of the short reads, which would lead to short
> reads of variable length because of different base quality at the 3' end.
>  Then, I tried to read in this second FASTQ file of reads of variable
> length.  It used up all of the 16 GB memory, and not using CPUs at all.  It
> seems there are some efficient code in readSeqFile as mentioned in the
> readSeqFile help message.  It seems to fall apart when short reads are of
> different size.
> >>
> >> I wish to see how the trimming change the base-quality plots, and this
> is a problem.  I am wondering if there is a way of sidestepping this
> problem.
> >>
> >> Thank you,
> >>
> >> SangChul
> >> _______________________________________________
> >> 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
Statistical Programmer
Bioinformatics Core
UC Davis Genome Center
vincebuffalo.com twitter.com/vsbuffalo

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