Identifying and mitigating batch effects in whole genome sequencing data
作者: Jennifer A. TomJens ReederWilliam F. ForrestRobert R. GrahamJulie HunkapillerTimothy W. BehrensTushar R. Bhangale
作者单位: 1Genentech Inc
刊名: BMC Bioinformatics, 2017, Vol.18 (1)
来源数据库: Springer Journal
DOI: 10.1186/s12859-017-1756-z
关键词: Whole genome sequencingGenotypingGenome-wide association studiesBatch effects
英文摘要: Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data.
原始语种摘要: Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data.
全文获取路径: Springer  (合作)
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影响因子:3.024 (2012)

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关键词翻译
关键词翻译
  • sequencing 排序
  • genome 基因组
  • batch 一批
  • whole 全部的
  • effects 海员自身物品
  • bioinformatics 生物信息学
  • remove 除去
  • association 联合
  • detect 探测
  • inevitably 不可避免地