I have 101 base reads and expect up to 20 mismatches to reference. My reads are not pairs. I have tried bwa bwasw -a 1 -b 1 -T 60 but it only aligns 1.5% of the reads. And those have only a couple mismatches. I know from other tests ~ 30% should be aligned with 20 mismatches. Is this just something bwa is not designed for? What would be a better aligner? Or am I not using the right settings?
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Maybe you try bfast or ssaha. They are not very fast but should perform ways better on your data. Bfast seems to be faster (from what I heard) but I think ssaha is a good startingpoint to get a first estimate of the alignment rate, because its very easy to use. Maybe you just try as subset at the beginning (100-1000kreads), because it's really not that fast.
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Originally posted by moritzhess View PostMaybe you try bfast or ssaha. They are not very fast but should perform ways better on your data. Bfast seems to be faster (from what I heard) but I think ssaha is a good startingpoint to get a first estimate of the alignment rate, because its very easy to use. Maybe you just try as subset at the beginning (100-1000kreads), because it's really not that fast.
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Originally posted by szilva View PostFor 20 mismatches per reads I would prefer something that is not based on Burrows-Wheeler, especially if you are expecting indels. Even for 101 bp long reads this amount of mismatches is pretty high.
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Feederbing, you can try novoalign. It will allow up to 10 high quality mismatches. Also have a look at some of the trimming options that could improve your mapping rate.
Do you have a good idea of the quality profile to see where quality starts dropping off ? FastqC is a good tool for examining this.
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Originally posted by feederbing View Postzee, just to be clear, the reason I expect so many mismatches is because of evolution, not sequencing quality.
Good luck
Dario
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101bp, 20% mismatches. I believe you will have lots of misalignments if you are aligning against human (fine if against a small genome). If you want to do that anyway, I would vote ssaha2.
BTW, to map high error rate with bwa-sw, you should decrease "-T" and increase "-z" to 10 or 100. Your setting may even make bwa-sw less sensitivity than the default setting. Nonetheless, even for -z100, probably bwa-sw would not work well for 100bp+20% mismatches.
For mammalian genomes, another option is BWT-SW. If you have short reference genome, you may try cross_match, fasta and SSE2-based smith-waterman.
If you have high coverage, you should assemble the reads first and then do alignment. That will be much better.
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Maybe Heng can correct me, but isn't bwasw for longer reads and should not be used for 100bp reads, especially with that expected error rate? (At least that's what I remember from his paper.)
As for increasing the -z value, I barely see improvements for values above 10 and the run time for higher values is not really worth it. It sometimes helps to rerun the program with the remaining reads to get more aligned.
Anybody has experience with SOAP2?
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