Statistical methods for analysis of high-throughput RNA interference screens
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Published on: November 28, 2016
Amanda Birmingham1, Laura M Selfors, Thorsten Forster
1The RNAi Global Initiative, Lafayette, Colorado, USA. amanda.birmingham@thermofisher.com
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.

