A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage
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Abstract
Background: The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage).
Results: We describe a computational method for finding common SNPs with allele frequencies in single-pass sequences of deep coverage. The method enhances a widely used program named PolyBayes in several aspects. We present results from our method and PolyBayes on eighteen data sets of human expressed sequence tags (ESTs) with deep coverage. The results indicate that our method used almost all single-pass sequences in computation of the allele frequencies of SNPs.
Conclusion: The new method is able to handle single-pass sequences of deep coverage efficiently. Our work shows that it is possible to analyze sequences of deep coverage by using pairwise alignments of the sequences with the finished genome sequence, instead of multiple sequence alignments.
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This article is published as Wang, Jianmin, and Xiaoqiu Huang. "A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage." BMC bioinformatics 6 (2005): 220. doi: 10.1186/1471-2105-6-220.