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An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing.

Nicholas HutsonFenglin ZhanJames GrahamMitsuko MurakamiHan ZhangSujana GanapartiQiang HuLi YanChangxing MaSong LiuJun XieLei Wei
Published in: BMC medical genomics (2021)
We developed a new adaptive method for distinguishing unknown from negative statuses in multi-sample comparison NGS data. The method can provide more accurate negative statuses than the conventional UMC method and generate a remarkably higher amount of available data by reducing unnecessary "unknown" calls.
Keyphrases
  • electronic health record
  • big data
  • gene expression
  • machine learning
  • copy number
  • artificial intelligence