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Statistical methods for analysis of high-throughput RNA interference screens

Authors :
Dara J. Dunican
Thorsten Forster
Javier Santoyo-Lopez
Aideen Long
Caleb J. Kennedy
Laura M. Selfors
Roderick L. Beijersbergen
Dermot Kelleher
Caroline E. Shamu
Queta Smith
Emma Shanks
David Wrobel
Peter Ghazal
Amanda Birmingham
Source :
Birmingham, A, Selfors, L M, Forster, T, Wrobel, D, Kennedy, C J, Shanks, E, Santoyo-Lopez, J, Dunican, D J, Long, A, Kelleher, D, Smith, Q, Beijersbergen, R L, Ghazal, P & Shamu, C E 2009, ' Statistical methods for analysis of high-throughput RNA interference screens ', Nature Methods, vol. 6, no. 8, pp. 569-575 . https://doi.org/10.1038/nmeth.1351
Publication Year :
2009

Abstract

RNA interference (RNAi) has become a powerful technique for reverse genetics and drug discovery, and in both of these areas large-scale high-throughput RNAi screens are commonly performed. The statistical techniques used to analyze these screens are frequently borrowed directly from small-molecule screening; however, small-molecule and RNAi data characteristics differ in meaningful ways. We examine the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis. Additionally, we provide guidance on selection of analysis techniques in the context of a sample workflow.

Details

Language :
English
Database :
OpenAIRE
Journal :
Birmingham, A, Selfors, L M, Forster, T, Wrobel, D, Kennedy, C J, Shanks, E, Santoyo-Lopez, J, Dunican, D J, Long, A, Kelleher, D, Smith, Q, Beijersbergen, R L, Ghazal, P & Shamu, C E 2009, ' Statistical methods for analysis of high-throughput RNA interference screens ', Nature Methods, vol. 6, no. 8, pp. 569-575 . https://doi.org/10.1038/nmeth.1351
Accession number :
edsair.doi.dedup.....3fad3553122354396e0bf911a7c2c37e