The use of strictly standardized mean difference for hit selection in primary RNA interference high-throughput screening experiments.
RNA interference (RNAi) high-throughput screening (HTS) has been hailed as the 2nd genomics wave following the 1st genomics wave of gene expression microarrays and single-nucleotide polymorphism discovery platforms. Following an RNAi HTS, the authors are interested in identifying short interfering RNA (siRNA) hits with large inhibition/activation effects. For hit selection, the z-score method and its variants are commonly used in primary RNAi HTS experiments. Recently, strictly standardized mean difference (SSMD) has been proposed to measure the siRNA effect represented by the magnitude of difference between an siRNA and a negative reference group. The links between SSMD and d+-probability offer a clear interpretation of siRNA effects from a probability perspective. Hence, SSMD can be used as a ranking metric for hit selection. In this article, the authors investigated both the SSMD-based testing process and the use of SSMD as a ranking metric for hit selection in 2 primary siRNA HTS experiments. The analysis results showed that, as a ranking metric, SSMD was more stable and reliable than percentage inhibition and led to more robust hit selection results. Using the SSMD -based testing method, the false-negative rate can more readily be obtained. More important, the use of the SSMD-based method can result in a reduction in both the false-negative and false-positive rates. The applications presented in this article demonstrate that the SSMD method addresses scientific questions and fills scientific needs better than both percentage inhibition and the commonly used z-score method for hit selection.
Zhang
Xiaohua Douglas
XD
Biometrics Research, Merck Research Laboratories, West Point, Pennsylvania 19486, USA. xiaohua_zhang @merck.com
Ferrer
Marc
M
Espeseth
Amy S
AS
Marine
Shane Douglas
SD
Stec
Erica M
EM
Crackower
Michael A
MA
Holder
Daniel J
DJ
Heyse
Joseph F
JF
Strulovici
Berta
B
D005188:False Negative Reactions; D005189:False Positive Reactions; D023281:Genomics; D016174:Hepacivirus / Q000235:genetics; D015233:Models, Statistical; D009077:Mucins / Q000235:genetics / Q000592:standards; D034622:RNA Interference / Q000502:physiology*; D012367:RNA, Viral / Q000235:genetics / Q000592:standards
D009077:Mucins; D012367:RNA, Viral