Considering Quality scores of reads when aligning

thinkRNA · 05-26-2010, 02:23 PM

I have reads with quality scale on phred64. I get an error when using --solexa1.3-quals option in tophat which is a known error (Error: could not execute prep_reads)

So, since I can't use this option, does it mean my reads get aligned without the quality scores being taken into consideration by bowtie?

Finally, how does one decide what is a good quality score? What if there are really bad quality reads in the seed region (beginning of the read) but good ones towards the end giving it a high quality score. In this case, I would like to throw this read .

Any one has any thoughts on threshold used?

maubp · 05-31-2010, 06:53 AM

I'm not sure what exactly TopHat would do in this situation.

You could try converting your reads from the Illumina 1.3+ FASTQ file format (aka phred64) to a Sanger FASTQ file (aka phred33).

There are lots of tools to do this conversion (search the forum), I'm biased but would suggest EMBOSS seqret for a command line tool, or for a script based solution BioPython (use function Bio.SeqIO.convert for this) or BioPerl etc.

mattanswers · 06-01-2010, 08:40 AM

In the following URL the is a graph relating Q score (Sanger and Solexa) with p-value: http://en.wikipedia.org/wiki/FASTQ_format
Basically, I think anything above a Q (solexa) score of 20 is very acceptable. From 20-13 the probability begins to vary much more. Around a Q score of 13 it seems that there is a 0.05 chance of a bad call.

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05-26-2010, 02:23 PM	#1
thinkRNA Member Location: Carlsbad,CA Join Date: Jan 2010 Posts: 94	Considering Quality scores of reads when aligning I have reads with quality scale on phred64. I get an error when using --solexa1.3-quals option in tophat which is a known error (Error: could not execute prep_reads) So, since I can't use this option, does it mean my reads get aligned without the quality scores being taken into consideration by bowtie? Finally, how does one decide what is a good quality score? What if there are really bad quality reads in the seed region (beginning of the read) but good ones towards the end giving it a high quality score. In this case, I would like to throw this read . Any one has any thoughts on threshold used? Last edited by thinkRNA; 05-26-2010 at 03:19 PM.

05-31-2010, 06:53 AM	#2
maubp Peter (Biopython etc) Location: Dundee, Scotland, UK Join Date: Jul 2009 Posts: 1,543	I'm not sure what exactly TopHat would do in this situation. You could try converting your reads from the Illumina 1.3+ FASTQ file format (aka phred64) to a Sanger FASTQ file (aka phred33). There are lots of tools to do this conversion (search the forum), I'm biased but would suggest EMBOSS seqret for a command line tool, or for a script based solution BioPython (use function Bio.SeqIO.convert for this) or BioPerl etc. Last edited by maubp; 06-01-2010 at 07:17 AM. Reason: corrected a typo

06-01-2010, 08:40 AM	#3
mattanswers Member Location: Boston Join Date: Oct 2009 Posts: 65	In the following URL the is a graph relating Q score (Sanger and Solexa) with p-value: http://en.wikipedia.org/wiki/FASTQ_format Basically, I think anything above a Q (solexa) score of 20 is very acceptable. From 20-13 the probability begins to vary much more. Around a Q score of 13 it seems that there is a 0.05 chance of a bad call.