中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
SNP calling using genotype model selection on high-throughput sequencing data

文献类型:期刊论文

作者You, Na2; Murillo, Gabriel1; Su, Xiaoquan3; Zeng, Xiaowei3; Xu, Jian3; Ning, Kang3; Zhang, Shoudong4; Zhu, Jiankang4,5; Cui, Xinping1,6
刊名BIOINFORMATICS
出版日期2012-03-01
卷号28期号:5页码:643-650
中文摘要

MOTIVATION: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for. RESULTS: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts for the errors that occur during the preparation of the genomic sample. Simulations and real data analyses indicate that GeMS has the best performance balance of sensitivity and positive predictive value among the tested SNP callers.

英文摘要Motivation: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base- calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base- calling or alignment, such as those in genomic sample preparation, are not accounted for.
WOS标题词Science & Technology ; Life Sciences & Biomedicine ; Technology ; Physical Sciences
学科主题功能基因组
类目[WOS]Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Statistics & Probability
研究领域[WOS]Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
关键词[WOS]DISCOVERY ; FRAMEWORK
收录类别SCI
语种英语
WOS记录号WOS:000300986600007
公开日期2012-11-22
源URL[http://ir.qibebt.ac.cn:8080/handle/337004/1419]  
专题青岛生物能源与过程研究所_单细胞中心
作者单位1.Univ Calif Riverside, Dept Stat, Riverside, CA 92521 USA
2.Sun Yat Sen Univ, Sch Math & Computat Sci, Dept Stat Sci, Guangzhou 510275, Guangdong, Peoples R China
3.Chinese Acad Sci, Qingdao Inst BioEnergy & Bioproc Technol, Qingdao 266101, Peoples R China
4.King Abdullah Univ Sci & Technol, Plant Stress Genom & Technol Res Ctr, Thuwal 239556900, Saudi Arabia
5.Purdue Univ, Dept Hort & Landscape Architecture, W Lafayette, IN 47907 USA
6.Univ Calif Riverside, Inst Integrat Genome Biol, Ctr Plant Cell Biol, Riverside, CA 92521 USA
推荐引用方式
GB/T 7714
You, Na,Murillo, Gabriel,Su, Xiaoquan,et al. SNP calling using genotype model selection on high-throughput sequencing data[J]. BIOINFORMATICS,2012,28(5):643-650.
APA You, Na.,Murillo, Gabriel.,Su, Xiaoquan.,Zeng, Xiaowei.,Xu, Jian.,...&Cui, Xinping.(2012).SNP calling using genotype model selection on high-throughput sequencing data.BIOINFORMATICS,28(5),643-650.
MLA You, Na,et al."SNP calling using genotype model selection on high-throughput sequencing data".BIOINFORMATICS 28.5(2012):643-650.

入库方式: OAI收割

来源:青岛生物能源与过程研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。