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Hiya!
I have a bunch of old RNAseq data sets that I want to re-analyse using our current pipeline. First challenge was that the data is old enough to have been archived in qseq format, not fastq. I converted all files using a neat little java tool found here:
Described here: http://www.biostars.org/p/6682/
Has worked well and is pretty fast. My resulting fastq files, however, contain every single read - including the one with low quality and those that have a failed p/f flag. Therefore I want to some quality trimming before I move on to analysis.
Does anyone have any tool recommendations? And, more importantly, a rational way of filtering? What would be a good quality cutoff to use? If I am not mistaken the quality scores spit out by the java tool are phred64.
Cheers!
TabeaK
I have a bunch of old RNAseq data sets that I want to re-analyse using our current pipeline. First challenge was that the data is old enough to have been archived in qseq format, not fastq. I converted all files using a neat little java tool found here:
Described here: http://www.biostars.org/p/6682/
Has worked well and is pretty fast. My resulting fastq files, however, contain every single read - including the one with low quality and those that have a failed p/f flag. Therefore I want to some quality trimming before I move on to analysis.
Does anyone have any tool recommendations? And, more importantly, a rational way of filtering? What would be a good quality cutoff to use? If I am not mistaken the quality scores spit out by the java tool are phred64.
Cheers!
TabeaK
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