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Navigable Slide Index

1. Introduction
2. Preface
3. Overview
4. Multiple testing - the problem
5. Combining p-values
6. Power of combining p-values
7. Issues with combining p-values
8. Modeling true gene effects
9. Issues with modeling true effects
10. False discovery rate
11. False discovery variance
12. Variance of BH method
13. Other approaches to the variance
14. Power and sample size for FDR
15. Sample sizes to detect at least one SNP
16. Other error measures
17. Q-values vs. local FDR
18. False positive report probability
19. Multiple correlated tests
20. Standard permutation test
21. Fitting analytic distributions
22. Simulating correlated p-values
23. Summary
24. References

Topics Covered

• Multiplicity
• Combining evidence
• False discovery rate
• Q-value and local FDR
• False positive report probability
• Permutation testing

Links

Series:

• Genetic Epidemiology II

Categories:

• Genetics & Epigenetics
• Methods

Talk Citation

Dudbridge, F. (2007, October 1). Detecting multiple associations in genome-wide studies [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved April 15, 2025, from https://doi.org/10.69645/VCYH8764.
Export Citation (RIS)

Publication History

• Published on October 1, 2007
• Archived on February 25, 2021

Financial Disclosures

• Prof. Frank Dudbridge has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.