title: A probability-based approach for the analysis of large-scale RNAi screens.
abstract: We describe a statistical analysis methodology designed to minimize the impact of off-target activities upon large-scale RNA interference (RNAi) screens in mammalian cells. Application of this approach enhances reconfirmation rates and facilitates the experimental validation of new gene activities through the probability-based identification of multiple distinct and active small interfering RNAs (siRNAs) targeting the same gene. We further extend this approach to establish that the optimal redundancy for efficacious RNAi collections is between 4-6 siRNAs per gene.
authors.affiliation: The Genomics Institute of the Novartis Research Foundation, 10675 John J Hopkins Drive, San Diego, California 92121, USA.
authors.forename: Renate
authors.initials: R
authors.lastname: König
authors.forename: Chih-yuan
authors.initials: CY
authors.lastname: Chiang
authors.forename: Buu P
authors.initials: BP
authors.lastname: Tu
authors.forename: S Frank
authors.initials: SF
authors.lastname: Yan
authors.forename: Paul D
authors.initials: PD
authors.lastname: DeJesus
authors.forename: Angelica
authors.initials: A
authors.lastname: Romero
authors.forename: Tobias
authors.initials: T
authors.lastname: Bergauer
authors.forename: Anthony
authors.initials: A
authors.lastname: Orth
authors.forename: Ute
authors.initials: U
authors.lastname: Krueger
authors.forename: Yingyao
authors.initials: Y
authors.lastname: Zhou
authors.forename: Sumit K
authors.initials: SK
authors.lastname: Chanda
mesh_terms: D000818:Animals; D011336:Probability; D034622:RNA Interference; D034741:RNA, Small Interfering / Q000235:genetics*