• Archived Lectures *These may not cover the latest advances in the field
• 38 min
  1. Segregation analysis

  • Prof. Chris Cannings
  • Dr. Dawn Teare
• 35 min
  2. Choosing the right study design in genetic epidemiology

  • Prof. Duncan Thomas
• 27 min
  3. Genome-wide scans

  • Prof. Michael Province
• 40 min
  4. The study of candidate genes in drug trials - sample size considerations

  • Prof. Robert Elston
• 48 min
  5. Graphical modelling of linkage disequilibrium

  • Prof. Alun Thomas
• 50 min
  6. Bayesian approaches for modelling complex metabolic pathways

  • Prof. Duncan Thomas
• 53 min
  7. Current methods for the analysis of genetic case-control data: a review

  • Prof. Duncan Thomas
• 44 min
  8. Detecting and correcting for population structure in genetic case-control studies

  • Dr. Jonathan Pritchard
• 57 min
  9. Statistical characterization of genetic association

  • Prof. Bruce Weir
• 34 min
  10. Haplotype-based mapping and pharmacogenetics

  • Prof. David Goldstein
• 50 min
  11. Genetic linkage analysis

  • Prof. Christopher Amos
• 30 min
  12. Use of DNA pooling in large-scale association studies

  • Prof. Pak Sham
• 29 min
  13. Searching for genetic association using (haplotype) tagging SNPs

  • Prof. David Clayton
• 27 min
  14. Heterogeneity: problems and solutions

  • Prof. Michael Province
• 37 min
  15. Introduction to population genetics 1: single locus

  • Prof. David Balding
  • Dr. Andrew Morris
• 57 min
  16. Haplotype phase inference

  • Prof. Peter Donnelly
• 38 min
  17. Optimal use of linkage disequilibrium, haplotypes, and integrated maps for positional cloning

  • Prof. Newton Morton
  • Dr. Andrew Collins
• 58 min
  18. Introductory genetics for statisticians

  • Prof. Robert Elston
• 30 min
  19. Nature, nurture, neither?

  • Prof. Steve Jones
• 35 min
  20. Introduction to population genetics 2: linkage disequilibrium

  • Prof. David Balding
  • Dr. Andrew Morris
• 34 min
  21. Fine-scale mapping

  • Prof. David Balding
  • Dr. Andrew Morris

Printable Handouts

PDF

Navigable Slide Index

1. Introduction
2. Background (1)
3. Background (2)
4. Example
5. Phase information
6. Methods for recovering phase information
7. Example: using pedigree information
8. Using population information
9. Approaches to inferring haplotypes
10. Computational methods: Clark's algorithm (1)
11. Computational methods: Clark's algorithm (2)
12. Computational methods: Clark's algorithm (3)
13. Other computational methods
14. Maximum likelihood (1)
15. Maximum likelihood (2)
16. Maximum likelihood: the EM algorithm
17. Bayesian approaches
18. General advantages of Bayesian methods
19. Conceptual issues in Bayesian methods
20. Markov chain Monte Carlo
21. PHASE
22. PHASE simulation studies
23. PHASE simulation studies: figure
24. Approximate coalescent prior
25. Approximate coalescent prior (Ctd)
26. Alternative Bayesian methods
27. Comparisons
28. Comparisons: table
29. Conclusions
30. Additional references, and web resources

Topics Covered

• The problem of haplotype phase prediction and inference of frequencies
• Computational methods: parsimony and Clark's algorithm
• Computational methods: maximum likelihood and the EM algorithm
• Computational methods: Bayesian approaches
• The advantages of a Coalescent-based prior
• Coping with large numbers of markers
• Review of available software

Links

Series:

• Genetic Epidemiology I

Categories:

• Genetics & Epigenetics
• Methods

Talk Citation

Publication History

• Published on September 1, 2004
• Archived on February 25, 2021

Financial Disclosures

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