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http://dx.doi.org/10.6109/jkiice.2013.17.12.3009

Genotype-Calling System for Somatic Mutation Discovery in Cancer Genome Sequence  

Park, Su-Young (Department of Computer Science & Statistics, Chosun University)
Jung, Chai-Yeoung (Department of Computer Science & Statistics, Chosun University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.12, 2013 , pp. 3009-3015 More about this Journal
Abstract
Next-generation sequencing (NGS) has enabled whole genome and transcriptome single nucleotide variant (SNV) discovery in cancer and method of the most fundamental being determining an individual's genotype from multiple aligned short read sequences at a position. Bayesian algorithm estimate parameter using posterior genotype probabilities and other method, EM algorithm, estimate parameter using maximum likelihood estimate method in observed data. Here, we propose a novel genotype-calling system and compare and analyze the effect of sample size(S = 50, 100 and 500) on posterior estimate of sequencing error rate, somatic mutation status and genotype probability. The result is that estimate applying Bayesian algorithm even for 50 of small sample size approached real parameter than estimate applying EM algorithm in small sample more accurately.
Keywords
NGS(Next-Generation Sequencing); Bayesian algorithm; EM algorithm; genotype-calling system;
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