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Old 11-06-2009, 10:40 PM   #1
MattB
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Default Dealing with 1-2bp of adaptor on reads...

Hi all,

I have a question related to SNP detection and Illumina short reads. We have a paired-end 54bp dataset, where we can trim larger adaptor sequence matches without too much difficulty. However, when only one or two base pairs at the end of reads are actually the first two bases of the adaptor sequence, it is impossible to detect it as adaptor, the reads align since it is only 1-2 mismatches and subsequently a candidate SNP is detected.

In the example below, the lowercase 'a' at the end represents the first adaptor base, which is detected as a SNP in the alignment.

ATGCAGATTGGAGATCTTAACACGCTCGa

Any ideas about how to filter such likely false positive SNPs, apart from excluding SNPs that are present ONLY in the last one or two bases of reads...?

Matt
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Old 11-07-2009, 09:59 AM   #2
nilshomer
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Quote:
Originally Posted by MattB View Post
Hi all,

I have a question related to SNP detection and Illumina short reads. We have a paired-end 54bp dataset, where we can trim larger adaptor sequence matches without too much difficulty. However, when only one or two base pairs at the end of reads are actually the first two bases of the adaptor sequence, it is impossible to detect it as adaptor, the reads align since it is only 1-2 mismatches and subsequently a candidate SNP is detected.

In the example below, the lowercase 'a' at the end represents the first adaptor base, which is detected as a SNP in the alignment.

ATGCAGATTGGAGATCTTAACACGCTCGa

Any ideas about how to filter such likely false positive SNPs, apart from excluding SNPs that are present ONLY in the last one or two bases of reads...?

Matt
If your alignments are in the SAM format, you can just trim the last few bases on all alignments. We do this in our lab for variant detection.
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Old 11-08-2009, 11:45 PM   #3
MattB
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thanks, I guess this is the only way to avoid these SNPs. I was hoping to keep every single base of good quality in each read (after known adaptor sequence was trimmed), but it will probably be easier in the long run to just trim these few bases rather than trying to filter the SNPs afterwards.
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