Genetic Association Studies
Monday, January 28 – Friday, February 1, 2013,
9:00AM – 12PM
Sackler Room 514
Instructors: Peter Castaldi, MD, MSc and Jessica Paulus, ScD
This course will introduce learners to the background concepts necessary to
conduct and interpret genetic association studies and genome wide association
studies (GWAS). Specific topics include quality control (QC) for genome-wide
genotype data, linkage disequilibrium and SNP-tagging, assessment and adjustment
for genetic ancestry, and an introduction to relevant statistical concepts and PLINK.
Emphasis will be on population-based genetic association studies.
Learning Objectives:
1.) Students will understand how to use publically available databases to access
relevant functional information about specific genetic variants.
2.) Students will understand how to conduct genetic association analysis, including
genome-wide association analysis, using PLINK.
3.) Students will understand the most commonly used study designs and statistical
analytic methods for testing genetic association.
4.) Students will understand basic issues related to cleaning and data quality checks
for genome-wide genotype data.
5.) Students will understand linkage disequilibrium, how it is quantified, and how it
relates to SNP tagging and genetic association studies.
6.) Students will understand how population stratification can lead to spurious
association results, how to assess for it, and how to adjust for it.
*This instructor will lead the class with another instructor walking around the class
available for troubleshooting and assistance
Day
Monday
Tuesday
Concepts
Introductions and
course overview
Case-control study
designs
Basic statistics for
genetic association
and multiple testing
Overview of
Computational Tools
(Unix, R)
Introduction to WebBased Resources
(UCSC Genome
Browser, LocusZoom)
PEDfile format
Linkage
Disequilibrium
Overview of
genotyping chip
design
MAPfile format
Wednesday
Thursday
Friday
Introduction to
HapMap
GWAS with
quantitative traits
Linear and logistic
regression
Confounding and
Adjustment in Genetic
Association Studies
Quantifying Genomic
Inflation Factor
QQ plots
Data cleaning for
genomewide
genotype data
Introduction to
Sequencing
Hardy-Weinberg
equilibrium
Population
Stratification
Skills
Conduct simple association
testing in PLINK
Plot local association results
using LocusZoom
Make a simple Manhattan
plot in R
Instructors
Jessica Paulus
Pete Castaldi
Use the Haploview program
to construct an LD plot for
the CFH gene
Use SNAP to identify proxy
SNPs for rs380390 in
HapMap genotype data
Locate the CFH gene in the
UCSC Genome Browser
Jessica Paulus
Pete Castaldi
Perform an eQTL analysis
with SNPs on Chromosome
17 and expression of the
ORMDL3 gene
Make a QQ plot in R
Jessica Paulus
Pete Castaldi
Visualize results in
WGAViewer
Perform an eQTL analysis
adjusted for gender
Perform quality control on
genomewide genotype data
Michael Cho
(Channing Lab)
Jessica Paulus
Pete Castaldi
Calculate principal
Jessica Paulus
components of population
Pete Castaldi
stratification with
Eigenstrat
*This instructor will lead the class with another instructor walking around the class
available for troubleshooting and assistance
Day
Monday
Time
9:00-9:10
Event
Introductions
9:10-9:30
9:30-9:50
Introduction to GWAS, Part 1
Introductory Exercise – Unix, R,
WinScp
Break
Group 1 Introductions
Basic GWAS Statistics and
Multiple Comparisons
Learning Exercise 1 – Basic
Association Testing and Results
Visualization
Break
Group 2 Introductions
Introduction to GWAS, Part 2
Learning Exercise 1 cont.
Review and Group 3
Introductions
Linkage Disequilibrium, HapMap
and Chip Design
Break
Group 4 Introductions
Learning Exercise 2 – Linkage
Disequilibrium and Proxy SNPs
Quantifying Linkage
Disequilibrium
Break
Learning Exercise 2 cont.
Recap of Days 1 & 2
Review and Group 3
Introductions
Learning Exercise 3 – GWAS with
a Quantitative Trait, Adjustment
for Confounding in GWAS
Break
Study Designs for GWAS
Break
Introduction to Population
Stratification
Learning Exercise 3 cont.
Review and Questions
9:50-10:00
10:00-10:10
10:10-10:30
10:30-10:50
Tuesday
10:50-11:00
11:00-11:10
11:10-11:30
11:30-12:00
9:00-9:20
9:20-9:50
9:50-10:00
10:00-10:10
10:10-10:30
10:30-10:50
Wednesday
10:50-11:00
11:00-11:40
11:40-12:00
9:00-9:10
9:10-9:50
9:50-10:00
10:00-10:50
10:50-11:00
11:00-11:20
Thursday
11:20-11:50
9:00-9:10
9:10-9:30
Instructors
Jessica Paulus
Pete Castaldi
Pete Castaldi
Jessica Paulus
Pete Castaldi
Jessica Paulus
Pete Castaldi
Pete Castaldi
Jessica Paulus
Jessica Paulus
Pete Castaldi
Jessica Paulus
Jessica Paulus
Michael Cho
(Channing Lab)
Jessica Paulus
Pete Castaldi
Data Cleaning and QC of GWAS
Data
*This instructor will lead the class with another instructor walking around the class
available for troubleshooting and assistance
Friday
9:35-9:50
Learning Exercise 4 – GWAS Data
Cleaning and QC
9:50-10:00
10:00-10:20
10:20-10:50
Break
Learning Exercise 4 cont.
Introduction to Sequencing
10:50-11:00
11:00-11:20
11:20-12:00
9:00-9:10
Break
Hardy-Weinberg equilibrium
Open
Review and Questions
9:10-9:30
Potpourri- Hardy-Weinberg,
Imputation, Meta-Analysis,
Population Stratification
Article Review
Break
Learning Exercise 6 – Population
Stratification
Functional Follow-up of GWAS
Hits
Break
Learning Exercise 6 – Population
Stratification
Closing, Evaluations
9:30-9:50
9:50-10:00
10:00-10:30
10:30-10:50
10:50-11:00
11:00-11:30
11:30-12:00
Michael Cho
(Channing Lab)
Michael Cho
(Channing Lab)
Jessica Paulus
Jessica Paulus
Pete Castaldi
Pete Castaldi
Pete Castaldi
*This instructor will lead the class with another instructor walking around the class
available for troubleshooting and assistance