1. General methods of SNP discovery: PolyBayes Gabor T. Marth Department of Biology Boston College Chestnut Hill, MA 02467
2. General methods of SNP mining – PolyBayes 2. Use sequence quality information ( base quality values ) to distinguish true mismatches from sequencing errors sequencing error true polymorphism 1. Utilize the genome reference sequence as a template to organize other sequence fragments from arbitrary sources Two innovative ideas:
3. Computational SNP mining – PolyBayes sequence clustering simplifies to database search with genome reference paralog filtering by counting mismatches weighed by quality values multiple alignment by anchoring fragments to genome reference SNP detection by differentiating true polymorphism from sequencing error using quality values
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8. SNP discovery with PolyBayes genome reference sequence 1. Fragment recruitment (database search) 2. Anchored alignment 3. Paralog identification 4. SNP detection
9. Bayesian-statistical SNP detection 1. The algorithm probability of polymorphism base call, base quality a priori polymorphism rate base composition depth of coverage
