Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- Acronyms and Abbreviations
- Part I RNAi HTS and Data Analysis
- 1 Introduction to Genome-Scale RNAi Research
- 2 Experimental Designs
- 3 Data Display and Normalization
- 4 Quality Control in Genome-Scale RNAi Screens
- 5 Hit Selection in Genome-Scale RNAi Screens without Replicates
- 6 Hit Selection in Genome-Scale RNAi Screens with Replicates
- Part II Methodological Development for Analyzing RNAi HTS Screens
- References
- Index
- Plate section
6 - Hit Selection in Genome-Scale RNAi Screens with Replicates
Published online by Cambridge University Press: 03 May 2011
- Frontmatter
- Contents
- Preface
- Acknowledgments
- Acronyms and Abbreviations
- Part I RNAi HTS and Data Analysis
- 1 Introduction to Genome-Scale RNAi Research
- 2 Experimental Designs
- 3 Data Display and Normalization
- 4 Quality Control in Genome-Scale RNAi Screens
- 5 Hit Selection in Genome-Scale RNAi Screens without Replicates
- 6 Hit Selection in Genome-Scale RNAi Screens with Replicates
- Part II Methodological Development for Analyzing RNAi HTS Screens
- References
- Index
- Plate section
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 ScreeningPractical Experimental Design and Data Analysis for Genome-Scale RNAi Research, pp. 83 - 108Publisher: Cambridge University PressPrint publication year: 2011
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