SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing data
作者: Yong ChenLi ZhaoYi WangMing CaoViolet GelowaniMingchu XuSmriti A. AgrawalYumei LiStephen P. DaigerRichard GibbsFei WangRui Chen
作者单位: 1Shanghai Key Lab of Intelligent Information Processing
2Fudan University
3Baylor College of Medicine
4University of Texas Health Science Center
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Nature Journal
DOI: 10.1186/s12859-017-1566-3
关键词: Next-generation sequencingCopy number variationMaximum penalized likelihood estimation
原始语种摘要: Targeted next-generation sequencing (NGS) has been widely used as a cost-effective way to identify the genetic basis of human disorders. Copy number variations (CNVs) contribute significantly to human genomic variability, some of which can lead to disease. However, effective detection of CNVs from targeted capture sequencing data remains challenging.
全文获取路径: Springer Nature  (合作)
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来源刊物:
影响因子:3.024 (2012)

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关键词翻译
关键词翻译
  • sequencing 排序
  • targeted 对准目标的
  • generation 世代
  • novel 长篇小说
  • number 号码
  • genomic 染色体组的
  • likelihood 似然
  • genetic 遗传的
  • variation 变异
  • widely 广泛地