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Navigable Slide Index

1. Introduction
2. Outline (1)
3. The hoped-for result of GWA
4. The problem: GWAS data are imperfect
5. The problem - quote
6. Outline (2)
7. Genotype calling
8. Genotypes are not raw data
9. Outline (3)
10. SNP QC information
11. Missing data as a quality metric
12. Hardy Weinberg equilibrium
13. Rare SNPs
14. A potentially interesting phenomenon?
15. Or a lab artefact?
16. SNP QC in practice: the WTCCC
17. WTCCC pre and post QC
18. Outline (4)
19. Sample filters
20. Identity by state (IBS)
21. MDS and ancestry
22. Sample gender
23. Sample QC in practice: the WTCCC
24. Outline (5)
25. Quality control for imputation
26. Low quality hapmap data affects imputation
27. Outline (6)
28. Software resources
29. References

Topics Covered

• Unfiltered GWA data lead to false positive associations
• SNP and genotype quality control, including imputation
• Sample quality control, including related individuals and ethnic outliers
• Quality control in the WTCCC
• Software for QC of GWA

Links

Series:

• Statistical Methods for the Analysis of Genome-Wide Association Studies

Categories:

• Genetics & Epigenetics
• Methods

Talk Citation

Publication History

• Published on June 4, 2008
• Archived on January 15, 2020

Financial Disclosures

• Dr. Jeffrey Barrett has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.