Hi,

This may be a bit dumb or missing the point but just selecting the first 5 million is kind of random isn't it? I mean where the reads map and what they are from is not known to you and they were not collected by the sequencer in a manner that is influenced by the nature of the sample?


Best Wishes,
David.

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On 9 Nov 2011, at 09:44, Hans-Rudolf Hotz wrote:

Hi Paul, Hi Peter

You might also wanna look at the 'FastqSampler' function in the Bioconductor 'ShortRead' package
http://bioconductor.org/packages/release/bioc/html/ShortRead.html

We are working (as part of our NGS pipeline redesign) on adding more Bioconductor functionalities to Galaxy. Unfortunately, it is very low on my pile of stuff to do, so it will take a while till it appears in the 'Tool Shed'.


Regards, Hans



On 11/08/2011 11:45 PM, Peter Cock wrote:
On Tue, Nov 8, 2011 at 10:26 PM, Austin Paul<austinpa@usc.edu>  wrote:
Hi Peter,

Thanks for the suggestion.  For example, I have a fastq file with 50 million
reads and I want to randomly select 5 million of them. It seems biopython
would very easily select a single or a handful of reads with the
Bio.SeqIO.index() function.  Would it also be able to do the job I am
interested in?

Austin

I think so, but you'd have to use Bio.SeqIO.index_db() which stores
the index in an SQLite dictionary rather than in memory which isn't
really viable here (unless you have a 64bit big memory machine?).
I don't think I've tried it with quite that many reads though...

Alternatively, if I understood her correctly, Jennifer pointed out you
can do this in Galaxy but it will take a lot of IO:

1. Convert FASTQ to tabular (4 lines per record ->  1 line per record)
2. Randomly select lines (each line is now a record so safe)
3. Convert tabular back to FASTQ

It should work though, and requires no additional programming.

Peter

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