Statistical considerations for high throughput screening data

Xian Jin Xie

Research output: Contribution to journalReview articlepeer-review


High throughput screening (HTS) is a widely used effective approach in genome-wide association and large scale protein expression studies, drug discovery, and biomedical imaging research. How to accurately identify candidate 'targets' or biologically meaningful features with a high degree of confidence has led to extensive statistical research in an effort to minimize both false-positive and false-negative rates. A large body of literature on this topic with in-depth statistical contents is available. We examine currently available statistical methods on HTS and aim to summarize some selected methods into a concise, easy-tofollow introduction for experimental biologists.

Original languageEnglish (US)
Pages (from-to)354-360
Number of pages7
JournalFrontiers of Biology in China
Issue number4
StatePublished - 2010


  • false-negative rate
  • false-positive rate
  • high throughput screen
  • predictive modeling
  • target discovery

ASJC Scopus subject areas

  • Biotechnology
  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Genetics


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