• View the Talks
• 31 min
  1. Designing a genome-wide association study

  • Dr. Chris Spencer
• 49 min
  2. Genotyping algorithms for genome wide association studies

  • Dr. Vincent Plagnol
• 35 min
  3. Statistical tests for association

  • Dr. Andrew Morris
• 32 min
  4. Population structure in genome-wide association studies

  • Dr. Dan Davison
• 33 min
  5. Imputation in genome-wide association analysis

  • Prof. Jonathan Marchini
• 58 min
  6. Assessing significance in genome-wide studies

  • Dr. David Evans
• 27 min
  7. Meta-analysis in genome-wide association studies: application to type 2 diabetes

  • Dr. Eleftheria Zeggini
• Archived Lectures *These may not cover the latest advances in the field
• 20 min
  8. Imputing genotypes in genome-wide association studies

  • Prof. Jonathan Marchini
• 20 min
  9. Quality control measures for GWAS

  • Dr. Jeffrey Barrett
• 31 min
  10. Copy number variation and association studies

  • Dr. Don Conrad

Printable Handouts

PDF

Navigable Slide Index

1. Inroduction
2. Outline
3. Finding disease genes
4. Successes and failures
5. Finding disease genes (2)
6. Theory
7. Human polymorphism
8. The basic idea
9. Using correlation between markers
10. A more complete picture
11. Exploiting linkage disequilibrium
12. The HapMap
13. The HapMap (2)
14. Recombination hotspots
15. The cost of genotyping
16. Outline (2)
17. Prerequisites
18. What are the choices or constraints?
19. Commercially available chips
20. Coverage
21. Coverage does not measure power
22. Simulation (HapGen)
23. HapGen
24. HapGen (2)
25. Simulations
26. Comparing coverage and power
27. Single and multi marker tests
28. Multi-marker tests
29. Interpreting simulation results
30. How to close to maximum power?
31. Exploiting public data
32. Imputation
33. Summary
34. Looking to the future

Topics Covered

• Background to association studies
• LD and the HapMap
• Designing a case-control study
• How many markers, how many individuals?
• Estimating power
• Factors that impact on power
• Utilising publicly available data

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

Financial Disclosures

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