A probability-based approach for the analysis of large-scale RNAi screens.
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.
König
Renate
R
The Genomics Institute of the Novartis Research Foundation, 10675 John J Hopkins Drive, San Diego, California 92121, USA.
Chiang
Chih-yuan
CY
Tu
Buu P
BP
Yan
S Frank
SF
DeJesus
Paul D
PD
Romero
Angelica
A
Bergauer
Tobias
T
Orth
Anthony
A
Krueger
Ute
U
Zhou
Yingyao
Y
Chanda
Sumit K
SK
D000818:Animals; D011336:Probability; D034622:RNA Interference; D034741:RNA, Small Interfering / Q000235:genetics*