SNP Calling, Genotype Calling, and Sample Allele Frequency Estimation from New-Generation Sequencing Data

被引：279

作者：

Nielsen, Rasmus ^{[1
,2
,3
,4
]}

Korneliussen, Thorfinn ^{[4
]}

Albrechtsen, Anders ^{[4
]}

Li, Yingrui ^{[1
]}

Wang, Jun ^{[1
,4
]}

机构：

[1] BGI Shenzhen, Shenzhen, Peoples R China

[2] Univ Calif Berkeley, Dept Integrat Biol, Berkeley, CA 94720 USA

[3] Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA

[4] Univ Copenhagen, Dept Biol, Copenhagen, Denmark

来源：

PLOS ONE | 2012年 / 7卷 / 07期

基金：

美国国家卫生研究院;

关键词：

ASSOCIATION; INFERENCE; IMPUTATION; SITES;

D O I：

10.1371/journal.pone.0037558

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We present a statistical framework for estimation and application of sample allele frequency spectra from New-Generation Sequencing (NGS) data. In this method, we first estimate the allele frequency spectrum using maximum likelihood. In contrast to previous methods, the likelihood function is calculated using a dynamic programming algorithm and numerically optimized using analytical derivatives. We then use a Bayesian method for estimating the sample allele frequency in a single site, and show how the method can be used for genotype calling and SNP calling. We also show how the method can be extended to various other cases including cases with deviations from Hardy-Weinberg equilibrium. We evaluate the statistical properties of the methods using simulations and by application to a real data set.

引用

页数：10

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