Error rates and powers in genome-scale RNAi screens.
For hit selection in genome-scale RNAi research, we do not want to miss small interfering RNAs (siRNAs) with large effects; meanwhile, we do not want to include siRNAs with small or no effects in the list of selected hits. There is a strong need to control both the false-negative rate (FNR), in which the siRNAs with large effects are not selected as hits, and the restricted false-positive rate (RFPR), in which the siRNAs with no or small effects are selected as hits. An error control method based on strictly standardized mean difference (SSMD) has been proposed to maintain a flexible and balanced control of FNR and RFPR. In this article, the authors illustrate how to maintain a balanced control of both FNR and RFPR using the plot of error rate versus SSMD as well as how to keep high powers using the plot of power versus SSMD in RNAi high-throughput screening experiments. There are relationships among FNR, RFPR, Type I and II errors, and power. Understanding the differences and links among these concepts is essential for people to use statistical terminology correctly and effectively for data analysis in genome-scale RNAi screens. Here the authors explore these differences and links.
Zhang
Xiaohua Douglas
XD
Biometrics Research, Merck Research Laboratories, West Point, Pennsylvania 19486, USA. xiaohua_zhang@merck.com
Marine
Shane D
SD
Ferrer
Marc
M
D003627:Data Interpretation, Statistical; D004353:Drug Evaluation, Preclinical; D005189:False Positive Reactions; D016678:Genome; D023281:Genomics / Q000379:methods*; D006801:Humans; D015233:Models, Statistical; D034622:RNA Interference; D034741:RNA, Small Interfering / Q000235:genetics
D034741:RNA, Small Interfering