Advanced Gene Mapping Course, Rockefeller University
Dec. 13-17, 2010
The course will be held every day from 9 a.m. to 5 p.m. in Room 302 of the Weiss Building on the Rockefeller University campus, located at 1230 York Ave. (entrance at 66th Street). On Monday evening a social gathering will be held at The Rockefeller University Faculty Club. Each session will start with a theoretical introduction followed by practical exercises. Instructors for the course are Goncalo Abecasis, Heather Cordell, Christoph Lange, Suzanne Leal and Shaun Purcell.
Monday – Dec. 13
Instructor - Shaun Purcell
Whole Genome Association analysis, analysis of population-based data qualitative traits; controlling for confounders; association analysis of rare variant data for complex traits, pathway analysis
Exercises: PLINK, PLINKSEQ, INRICH
5:30PM Get-together for course participants and instructors at The Rockefeller Faculty Club.
Tuesday – Dec. 14
Instructor - Suzanne Leal
Data quality control for genome-wide association studies; gene x gene interaction (linear and logistic regression, MDR); sample size and power estimation (main effects & gene x gene and gene x environmental interaction); controlling the family wise error rate; false discovery rate; replication and analysis of rare variants complex traits association studies using next generation sequence data.
Exercises: PLINK, R, MDR, Quanto, Armitage test for trend power tool
Wednesday – Dec. 15
Instructor - Christoph Lange
Family-based association analysis of quantitative and qualitative traits; analysis of copy number variants
Thursday – Dec. 16
Instructor - Goncalo Abecasis
Imputation of genotype data for pedigrees and case-control data; meta analysis of association data; association analysis of population and family based data; power calculations for two stage genome-wide association studies; variant calling for association studies using sequence data.
Exercises: Merlin, MACH, MINIMAC, Metal, LAMP, CaTS
Friday – Dec. 17
Instructor - Heather Cordell
Whole genome association studies of quantitative traits population and family-based data; analysis of haplotype data; controlling for population admixture/substructure
Exercises: GenABEL, QTDT, Eigenstrat