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题名: Bayexer: an accurate and fast Bayesian demultiplexer for Illumina sequences
作者: Yi, Haisi1, 2; Li, Zhe3; Li, Tao1; Zhao, Jindong1, 4
刊名: BIOINFORMATICS
发表日期: 2015-12-15
DOI: 10.1093/bioinformatics/btv501
卷: 31, 期:24, 页:4000-4002
收录类别: SCI
文章类型: Article
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
英文摘要: Demultiplexing is used after high-throughput sequencing to in silico assign reads to the samples of origin based on the sequenced reads of the indices. Existing demultiplexing tools based on the similarity between the read index and the reference index sequences may fail to provide satisfactory results on low-quality datasets. We developed Bayexer, a Bayesian demultiplexing algorithm for Illumina sequencers. Bayexer uses the information extracted directly from the contaminant sequences of the targeting reads as the training dataset for a naive Bayes classifier to assign reads. According to our evaluation, Bayexer provides higher capability, accuracy and speed on various real datasets than other tools.
语种: 英语
项目资助者: Autonomous Projects of the State Key Laboratory of Freshwater Ecology and Biotechnology(2011FBZ31 ; 2011FBZ32)
WOS记录号: WOS:000366630400019
ISSN号: 1367-4803
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.ihb.ac.cn/handle/342005/27527
Appears in Collections:水生生物分子与细胞生物学研究中心_期刊论文

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作者单位: 1.Chinese Acad Sci, Inst Hydrobiol, Key Lab Algal Biol, Wuhan 430072, Hubei, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Bot, State Key Lab Systemat & Evolutionary, Beijing 100093, Peoples R China
4.Peking Univ, Coll Life Sci, Beijing 100871, Peoples R China
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