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6 - Hit Selection in Genome-Scale RNAi Screens with Replicates

Published online by Cambridge University Press:  03 May 2011

Xiaohua Douglas Zhang
Affiliation:
Merck Research Laboratories, Pennsylvania
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Summary

In Chapter 5, we discussed analytic methods for hit selection in screens without replicates. Analytic methods for hit selection in screens with replicates differ from those without replicates, mainly because we can directly estimate data variability for a tested siRNA based on multiple measured values of a phenotype for an siRNA in a screen with replicates, but we cannot do so for a screen without replicates. In a primary screen without replicates, we must make a strong assumption that each siRNA has the same variability as a negative reference group in a plate and use the variability of this negative reference to represent the variability of each siRNA. In a screen with replicates, the analytic methods do not rely on this assumption, and thus we can use more powerful methods.

In this chapter, I present analytic methods for hit selection in screens with replicates. Specifically, I provide metrics for hit selection in screens with replicates in Section 6.1, in which the focus is on the classical t-statistic and the SSMD method. In Section 6.2, I present a dual-flashlight plot in which both mean difference and SSMD are displayed, and in Section 6.3, I elaborate on various decision rules and associated false-positive and false-negative rates. In Section 6.4, I explore false discovery and false nondiscovery rates; in Section 6.5, I investigate sample size determination in screens with replicates; and in Section 6.6, I present SSMD-based statistical methods for adjusting for off-target effects.

Type
Chapter
Information
Optimal High-Throughput Screening
Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research
, pp. 83 - 108
Publisher: Cambridge University Press
Print publication year: 2011

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