A fast and accurate SNP detection algorithm for next-generation sequencing data

被引：33

作者：

Xu, Feng ^{[1
,2
]}

Wang, Weixin ^{[1
,2
]}

Wang, Panwen ^{[1
,2
]}

Li, Mulin Jun ^{[1
,2
]}

Sham, Pak Chung ^{[3
,4
,5
]}

Wang, Junwen ^{[1
,2
,3
,6
]}

机构：

[1] Univ Hong Kong, LKS Fac Med, Dept Biochem, Hong Kong, Hong Kong, Peoples R China

[2] Univ Hong Kong, Shenzhen Inst Res & Innovat, Shenzhen, Peoples R China

[3] Univ Hong Kong, LKS Fac Med, Ctr Genom Sci, Hong Kong, Hong Kong, Peoples R China

[4] Univ Hong Kong, LKS Fac Med, Dept Psychiat, Hong Kong, Hong Kong, Peoples R China

[5] Univ Hong Kong, State Key Lab Cognit & Brain Sci, Hong Kong, Hong Kong, Peoples R China

[6] Univ Hong Kong, HKU BGI Bioinformat Algorithms & Core Technol Res, Hong Kong, Hong Kong, Peoples R China

来源：

NATURE COMMUNICATIONS | 2012年 / 3卷

关键词：

SINGLE NUCLEOTIDE POLYMORPHISMS; GENOME-WIDE ASSOCIATION; HAPLOTYPE MAP; FRAMEWORK; ALIGNMENT; GENOTYPE; COVERAGE; REGIONS;

D O I：

10.1038/ncomms2256

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：

070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];

摘要：

Various methods have been developed for calling single-nucleotide polymorphisms from next-generation sequencing data. However, for satisfactory performance, most of these methods require expensive high-depth sequencing. Here, we propose a fast and accurate single-nucleotide polymorphism detection program that uses a binomial distribution-based algorithm and a mutation probability. We extensively assess this program on normal and cancer next-generation sequencing data from The Cancer Genome Atlas project and pooled data from the 1,000 Genomes Project. We also compare the performance of several state-of-the-art programs for single-nucleotide polymorphism calling and evaluate their pros and cons. We demonstrate that our program is a fast and highly accurate single-nucleotide polymorphism detection method, particularly when the sequence depth is low. The program can finish single-nucleotide polymorphism calling within four hours for 10-fold human genome next-generation sequencing data (30 gigabases) on a standard desktop computer.

引用

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