Normalizing RNA-sequencing data by modeling hidden covariates with prior knowledge.
作者: Sara MostafaviAlexis BattleXiaowei ZhuAlexander E UrbanDouglas LevinsonStephen B MontgomeryDaphne Koller
刊名: PLoS ONE, 2017, Vol.8 (7)
来源数据库: Directory of Open Access Journals
DOI: 10.1371/journal.pone.0068141
原始语种摘要: Transcriptomic assays that measure expression levels are widely used to study the manifestation of environmental or genetic variations in cellular processes. RNA-sequencing in particular has the potential to considerably improve such understanding because of its capacity to assay the entire transcriptome, including novel transcriptional events. However, as with earlier expression assays, analysis of RNA-sequencing data requires carefully accounting for factors that may introduce systematic, confounding variability in the expression measurements, resulting in spurious correlations. Here, we consider the problem of modeling and removing the effects of known and hidden confounding factors from RNA-sequencing data. We describe a unified residual framework that encapsulates existing...
全文获取路径: DOAJ  (合作)
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影响因子:3.73 (2012)

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关键词翻译
关键词翻译
  • sequencing 排序
  • RNA ROYAL NEPAL AIRLINES CORP.
  • expression 表示
  • hidden 潜伏的
  • genetic 遗传的
  • modeling 制祝型
  • accounting 会计
  • known 己知
  • novel 长篇小说
  • framework 构架