Article
Improving SNP discovery by base alignment quality.
Bioinformatics (Oxford, England) - 15 Apr 2011
Li Heng
Abstract excerpt
UNLABELLED: I propose a new application of profile Hidden Markov Models in the area of SNP discovery from resequencing data, to greatly reduce false SNP calls caused by misalignments around insertions and deletions (indels). The central concept is per-Base Alignment Quality, which accurately measures the probability of a read base being wrongly aligned. The effectiveness of BAQ has been positively confirmed on...
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