Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens

Xiaohua Douglas Zhang, Amy S. Espeseth, Eric N. Johnson, Jayne Chin, Adam Gates, Lyndon J. Mitnaul, Shane D. Marine, Jenny Tian, Eric M. Stec, Priya Kunapuli, Dan J. Holder, Joseph F. Heyse, Berta Strulovici, Marc Ferrer

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research.

Original languageEnglish
Pages (from-to)378-389
Number of pages12
JournalJournal of Biomolecular Screening
Volume13
Issue number5
DOIs
StatePublished - Aug 2008

Keywords

  • Plate design
  • Quality control
  • RNAi high-throughput screening
  • Strictly standardized mean difference
  • Z factor

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biotechnology
  • Biochemistry
  • Molecular Medicine
  • Pharmacology
  • Drug Discovery

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