MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data

doi:10.1093/bioinformatics/btv753

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	MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data
	Murillo, Gabriel H.1; You, Na 2; Su, Xiaoquan3 ; Cui, Wei 1; Reilly, Muredach P.4; Li, Mingyao 5; Ning, Kang 6; Cui, Xinping 1,7
	2016-05-15
发表期刊	BIOINFORMATICS
卷号	32 期号:10 页码:1486-1492
摘要	Motivation: Single nucleotide variant (SNV) detection procedures are being utilized as never before to analyze the recent abundance of high-throughput DNA sequencing data, both on single and multiple sample datasets. Building on previously published work with the single sample SNV caller genotype model selection (GeMS), a multiple sample version of GeMS (MultiGeMS) is introduced. Unlike other popular multiple sample SNV callers, the MultiGeMS statistical model accounts for enzymatic substitution sequencing errors. It also addresses the multiple testing problem endemic to multiple sample SNV calling and utilizes high performance computing (HPC) techniques.
文章类型	Article
WOS标题词	Science & Technology ; Life Sciences & Biomedicine ; Technology ; Physical Sciences
DOI	10.1093/bioinformatics/btv753
关键词[WOS]	DISCOVERY ; FRAMEWORK
收录类别	SCI
语种	英语
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
项目资助者	National Science Foundation(ATD1222718) ; University of California, Riverside [AES-CE RSAP](A01869) ; National Science Foundation of China [NSFC](11301554 ; Ministry of Science and Technology [high-tech (863) grant](2012AA023107 ; Sino-German Research Center(GZ878) ; Huazhong University of Science and Technology [start-up fund] ; (R01HG113147) ; NSFC 61103167 ; 2014AA021502) ; 31271410 ; 31401076)
WOS类目	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Statistics & Probability
WOS记录号	WOS:000376656900007
引用统计
文献类型	期刊论文
条目标识符	http://ir.qibebt.ac.cn/handle/337004/8229
专题	单细胞中心组群
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, Shandong, Peoples R China 4.Univ Penn, Perelman Sch Med, Cardiovasc Inst, Philadelphia, PA 19104 USA 5.Univ Penn, Perelman Sch Med, Dept Biostat & Epidemiol, Philadelphia, PA 19104 USA 6.Huazhong Univ Sci & Technol, Coll Life Sci & Technol, Key Lab Mol Biophys, Minist Educ, Wuhan 430074, Hubei, Peoples R China 7.Univ Calif Riverside, Inst Integrat Genome Biol, Ctr Plant Cell Biol, Riverside, CA 92521 USA
推荐引用方式 GB/T 7714	Murillo, Gabriel H.,You, Na,Su, Xiaoquan,et al. MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data[J]. BIOINFORMATICS,2016,32(10):1486-1492.
APA	Murillo, Gabriel H..,You, Na.,Su, Xiaoquan.,Cui, Wei.,Reilly, Muredach P..,...&Cui, Xinping.(2016).MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data.BIOINFORMATICS,32(10),1486-1492.
MLA	Murillo, Gabriel H.,et al."MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data".BIOINFORMATICS 32.10(2016):1486-1492.