Statistical methods for analysis of high-throughput RNA interference screens.
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.
Birmingham
Amanda
A
The RNAi Global Initiative, Lafayette, Colorado, USA. amanda.birmingham@thermofisher.com
Selfors
Laura M
LM
Forster
Thorsten
T
Wrobel
David
D
Kennedy
Caleb J
CJ
Shanks
Emma
E
Santoyo-Lopez
Javier
J
Dunican
Dara J
DJ
Long
Aideen
A
Kelleher
Dermot
D
Smith
Queta
Q
Beijersbergen
Roderick L
RL
Ghazal
Peter
P
Shamu
Caroline E
CE
D000818:Animals; D003198:Computer Simulation; D015233:Models, Statistical; D034622:RNA Interference; D034741:RNA, Small Interfering / Q000737:chemistry* / Q000235:genetics*; D012107:Research Design / Q000706:statistics & numerical data*; D054852:Small Molecule Libraries
D034741:RNA, Small Interfering; D054852:Small Molecule Libraries