title: Hit selection with false discovery rate control in genome-scale RNAi screens.
abstract: RNA interference (RNAi) is a modality in which small double-stranded RNA molecules (siRNAs) designed to lead to the degradation of specific mRNAs are introduced into cells or organisms. siRNA libraries have been developed in which siRNAs targeting virtually every gene in the human genome are designed, synthesized and are presented for introduction into cells by transfection in a microtiter plate array. These siRNAs can then be transfected into cells using high-throughput screening (HTS) methodologies. The goal of RNAi HTS is to identify a set of siRNAs that inhibit or activate defined cellular phenotypes. The commonly used analysis methods including median +/- kMAD have issues about error rates in multiple hypothesis testing and plate-wise versus experiment-wise analysis. We propose a methodology based on a Bayesian framework to address these issues. Our approach allows for sharing of information across plates in a plate-wise analysis, which obviates the need for choosing either a plate-wise or experimental-wise analysis. The proposed approach incorporates information from reliable controls to achieve a higher power and a balance between the contribution from the samples and control wells. Our approach provides false discovery rate (FDR) control to address multiple testing issues and it is robust to outliers.
authors.affiliation: Biometrics Research, Merck Research Laboratories, West Point, PA 19486, USA. Xiaohua_zhang@merck.com
authors.forename: Xiaohua Douglas
authors.initials: XD
authors.lastname: Zhang
authors.forename: Pei Fen
authors.initials: PF
authors.lastname: Kuan
authors.forename: Marc
authors.initials: M
authors.lastname: Ferrer
authors.forename: Xiaohua
authors.initials: X
authors.lastname: Shu
authors.forename: Yingxue C
authors.initials: YC
authors.lastname: Liu
authors.forename: Adam T
authors.initials: AT
authors.lastname: Gates
authors.forename: Priya
authors.initials: P
authors.lastname: Kunapuli
authors.forename: Erica M
authors.initials: EM
authors.lastname: Stec
authors.forename: Min
authors.initials: M
authors.lastname: Xu
authors.forename: Shane D
authors.initials: SD
authors.lastname: Marine
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Holder
authors.forename: Berta
authors.initials: B
authors.lastname: Strulovici
authors.forename: Joseph F
authors.initials: JF
authors.lastname: Heyse
authors.forename: Amy S
authors.initials: AS
authors.lastname: Espeseth
mesh_terms: D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D016679:Genome, Viral; D023281:Genomics / Q000379:methods*; D006678:HIV / Q000235:genetics; D006367:HeLa Cells; D016174:Hepacivirus / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D034622:RNA Interference; D034741:RNA, Small Interfering / Q000032:analysis; D012372:ROC Curve
chemical_list: D034741:RNA, Small Interfering