• 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. Linkage disequilibrium
3. Outline of talk
4. Notation
5. Relative risk models for multiple linked loci
6. Directed acyclical graphs (DAGs)
7. Fitting methods for case-control data
8. Haplotype assignment
9. Full likelihood for haplotype model
10. Likelihoods for haplotype associations
11. Prospective vs. retrospective likelihoods
12. E-M estimation of haplotypes
13. MCMC approach to haplotyping
14. Hierarchical models for multilocus genotypes
15. Illustration using DAGs
16. Extensions of genotype hierarchical models
17. Haplotypes vs. genotypes: relative efficiency
18. Haplotypes vs. genotypes: example
19. Bayesian smoothing and clustering models
20. Multiple comparisons and Bayesian smoothing
21. Conditional autoregressive (CAR) model
22. Illustration using DAGs
23. Example using simulated data
24. Mutation mapping
25. Illustration using DAGs
26. Spatial clustering models
27. Hierarchical clustering models
28. Bayesian spatial clustering using potts model (1)
29. Bayesian spatial clustering using potts model (2)
30. Illustration using DAGs
31. Voronoi model
32. Illustration using DAGs
33. Spatial clustering figure (1)
34. Spatial clustering figure (2)
35. Spatial clustering figure (3)
36. Spatial clustering figure (4)
37. Spatial clustering figure (5)
38. Spatial clustering figure (6)
39. Spatial clustering figure (7)
40. Spatial clustering figure (8)
41. Efficacy of spatial clustering: 1 functional mutation
42. Example using cystic fibrosis data
43. Efficacy of spatial clustering: 2 functional mutations
44. Combined potts and Voronoi model
45. Coalescent methods
46. The coalescent (1)
47. The coalescent (2)
48. Graphical representation of ancestral relationships
49. Ancestral recombination graphs
50. Graphical representation of ancestral relationships
51. Ancestral recombination graphs
52. Approximate bayesian computation
53. Conceptual model for LD mapping
54. Approximate coalescent methods
55. Illustration using case-control data
56. Disease mapping by ancestral inference
57. Haplotype sharing methods
58. Haplotype sharing
59. Haplotype sharing correlation
60. Example of application
61. "Star-shaped" genealogy assumption
62. Coalescent approximation
63. Illustration using DAGs
64. Haplotype blocks, htSNPs, and the HapMap project
65. Haplotype blocks and htSNPs
66. Example from Jeffries et al., (2001)
67. Example from Daly et al., (2001)
68. International haplotype mapping project ("HapMap")
69. HapMap in the news (1)
70. HapMap in the news (2)
71. HapMap: "common disease common variant"
72. HapMap objectives
73. Haplotype-tagging SNPs (htSNPs)
74. Is this a reasonable expectation?
75. htSNP selection criteria
76. Performance of SNP selection
77. Multi-ethnic cohort study (1)
78. Multi-ethnic cohort study (2)
79. Genotyping strategy
80. Example: CYP19 and breast cancer (1)
81. Hormone synthesis pathways
82. Example: CYP19 and breast cancer (2)
83. Example: CYP19 and breast cancer (3)
84. Example: CYP19 and breast cancer (4)
85. CYP19 block 1 haplotypes
86. CYP19 blocks 1-3: association with breast cancer
87. CYP19 long-range haplotypes
88. The spectrum of gene association studies
89. Future work

Topics Covered

• Genotype vs. haplotype penetrance models
• Likelihoods and fitting methods for case-control data
• Bayesian smoothing and clustering models
• Coalescent methods
• Haplotype sharing methods
• Haplotype blocks, htSNPs and the HapMap project

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. Duncan Thomas has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.