Statistical methods for analysis of high-throughput RNA interference screens
Nature MethodsPublished 30 July 2009Open access
Amanda Birmingham, Laura M. Selfors, Thorsten Forster, David M. Wrobel, Caleb J. Kennedy, Emma Shanks
Citations588
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TL;DR
This work examines the similarities and differences between RNAi and small-molecule screens, highlighting particular characteristics of RNAi screen data that must be addressed during analysis and provides guidance on selection of analysis techniques in the context of a sample workflow.
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.
Keywords
Biochemistry, Genetics and Molecular Biology
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