Registration for this module closes July 7. 

Live session timeframe (exact schedule with live sessions will be posted by module instructors prior to the start of the module): Wednesday: 11:30 a.m.-2:30 p.m. Pacific (2:30-5:30 p.m. Eastern); Thursday, 8 a.m. – 2:30 p.m. Pacific  (11 a.m. – 5:30 p.m. Eastern); Friday, 8 a.m. – 2:30 p.m. Pacific (11 a.m. – 5:30 p.m. Eastern).

This module serves as a foundation for many of the later modules. It includes:

• A unified treatment for the analysis of discrete genetic data, starting with estimates and sample variances of allele frequencies to illustrate genetic vs statistical sampling and Bayesian approaches.
• A detailed look at Hardy-Weinberg and linkage disequilibrium, including the use of exact tests with mid-p-values and a new look at X-chromosome Hardy-Weinberg testing.
• A new characterization of population structure with F-statistics, based on allelic matching within and between populations with individual inbreeding and relationship estimation as a special case.
• Analyses illustrated with applications to forensic science and association mapping, with particular reference to rare variants.

Concepts illustrated with R exercises. Suggested pairing: Modules 6, 8 and all later modules.

Learning Objectives: After attending this module, participants will be able to:

1. Estimate allele frequencies from genotype counts, including the case of allelic dominance, and estimate the within-population inbreeding coefficient.
2. Determine the sample size needed to detect a specified level of within-population inbreeding with a goodness-of-fit test for Hardy-Weinberg equilibrium.
3. Use publicly-available software to conduct an exact test for Hardy-Weinberg equilibrium.
4. Predict kinship levels for pairs of individuals in simple pedigrees, and identify reference data to estimate kinship from SNP genotype profiles. Identify estimation methods used by publicly-available software and select methods appropriate for particular study.
5. Calculate allele-matching proportions within and between individuals and populations at single loci from genotype counts in order to estimate population-structure parameters. Evaluate the population-structure estimation methods used in publicly-available software.