SNP calling using genotype model selection on high-throughput sequencing data | |
You, Na2; Murillo, Gabriel1; Su, Xiaoquan3; Zeng, Xiaowei3; Xu, Jian3; Ning, Kang3; Zhang, Shoudong4; Zhu, Jiankang4,5; Cui, Xinping1,6 | |
刊名 | BIOINFORMATICS |
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. |
学科主题 | 功能基因组 |
WOS标题词 | Science & Technology ; Life Sciences & Biomedicine ; Technology ; Physical Sciences |
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 |
内容类型 | 期刊论文 |
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. |
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