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Instructional Program

Daily Schedule

7:30 – 8:00
8:00 – 9:45  
9:45 – 10:15
10:15 – 12:00
12:15 – 1:00 p.m.
1:00 – 2:45     
2:45 – 3:15 
3:15 – 5:00   
6:30 

Coffee and registration
Lecture / Lab
Break
Lecture / Lab
Lunch
Lecture / Lab
Break
Lecture / Lab (except for Tuesday, May 29th)
Dinner (Tuesday, May 29th and Thursday, May 31st)

Instructional Program

Day 1 – May 28th
Introductory Concepts in Human Populations and Medical Genomics

Instructor: Laurent Excoffier
Time: 8:00 – 12:00
Place: Room 1

  • Principles of population genetics: This lecture will cover some of the major concepts in human population genetics including random genetic drift and the derivation and properties of the basic coalescence model.
    • Random Genetic Drift
      • The Hardy-Weinberg equilibrium law
      • The Wright-Fisher Model of random genetic drift
      • Effective population size
    • Gene trees and the basic coalescence model
      • Coalescence under different demographic scenarios (e.g. population growth)

Introductory Concepts in Genetic Epidemiology
Instructors: Alexandre Alcaïs and Hélène Vézina
Time: 13:00 – 17:00
Place: Room 1

  • We will first briefly introduce concepts and designs to study familial aggregation followed by basic principles of linkage and association analysis for qualitative traits. Topics covered will include designs and analytical methods used to study genetic linkage. Both parametric and non-parametric linkage analysis will be covered.
  • Presentation of the concepts will be followed by a computer lab application using real data an durrently availabe software such as MLB.
  • Finally, a brief introduction to the BALSAC genealogical resource and presentation of existing tools for their analysis will be presented.

Day 2 – May 29th
Introductory Concepts in Human Populations and Medical Genomics

Instructors: Luis B. Barreiro and Lluis Quintana-Murci
Time: 8:00 – 12:00
Place: Room 1

  • Human population genomics: This lecture will introduce the students to the most recent genomic datasets on human genome diversity. We will discuss the contribution of HapMap and the 1000 Genomes Project to the better understanding of human evolution and the development of genome-wide association studies. The following concepts will be presented:
    • Mutation and recombination
    • Recombination at pedigree level - concept of linkage disequilibrium (LD)
    • Measures of LD and its decay
    • Tagging SNPs
    • Population mutation parameter, population recombination rate

The lab will introduce methods of analyzing data from the HapMap project.

  • Demography of human populations: This lecture will introduce the different models to explain human evolution. It will give an overview of the most recent genetic data explaining the human origins and migration patterns. It will concentrate on phylogeographic studies, mostly concerning uniparentally-inherited genomes.

Introductory Concepts in Genetic Epidemiology
Instructor: Alexandre Alcaïs
Time: 13:00 – 16:15
Place: Room 1

  • This lecture will cover designs and analytic methods for genetic association studies. Methods to investigate direct (candidate locus) and indirect (linkage disequilibrium mapping) associations with human disease will be introduced. Both family-based and population-based designs will be presented.
  • Presentation of the concepts will be followed by a computer lab application using real data and currently available software such as FBAT.

Invited Lecture
Speaker: Ellen Wijsman
Time: 16:30 – 18:00
Place: Albert-Royer Auditorium at CHU Sainte-Justine (3175 Côte-Ste-Catherine Road)

Day 3 –May 30th
(Concurrent Sessions – lectures and computer labs, except for the first session)

Presentation of current research by a Faculty member in Population Genomics
Speaker: Laurent Excoffier
Title: The complex making of humans: relationships with archaic hominins
Time
: 8:00 – 8:40
Place: Room 1

Advanced Concepts in Population Genomics
Instructors: Laurent Excoffier, Nicolas Lartillot, and Luis B. Barreiro
Time: 8:45 – 17:00
Place: Room 1

  • Extension of the coalescence theory: this lecture will cover the following topics:
    • Probabilistic modeling in population genetics: principles of simulation, maximum likelihood and Bayesian inference.
    • Simple applications to coalescent: estimation of the effective population size, Ne and of demographic history with practical demonstrations, e.g. using Beast.
    • Briefly touching upon approximate Bayesian computation (ABC), to point out its main connection with, and its specificities compared to, regular Bayesian methods.
  • How to infer demography from genetic data: This lecture will describe how simulation-based approaches can help elucidate human evolution and the demographic history of different human groups.
  • Methods to detect natural selection (part I): This lecture will present the different statistical methods that can be used to identify signatures of natural selection in the human genome.
    • Inter-species neutrality tests.
    • Sequence-based neutrality tests.
    • Composite-likelihood methods.
    • Population differentiation levels.
    • LD-based approaches.

Advanced Concepts in Genetic Epidemiology and Statistical Genetics
Instructors: Marie-Hélène Roy-Gagnon, Aurélie Labbe and Alexandre Alcaïs
Time: 8:45 – 17:00
Place: Room 2

  • Introduction to quantitative genetics theory and linkage, and assocation analysis for quantitative traits.
    • This session will introduce key concepts and models in quantitative genetics and will cover usual methods for genetic linkage and association analysis of quantitative traits. During the session participants will also have the opportunity to use software implementing these methods, such as MERLIN and QTDT, in a computer lab.
  • Analysis of gene-environment interactions
    • In the first part of the lecture, we will review biological and statistical definitions of gene-gene (GxG) interaction (often called epistasis) and gene-environment (GxE) interactions for qualitative and quantitative traits. We will then discuss the reasons for modelling GxE and GxG interactions in genetic studies.
    • In the second part of the lecture, the participants will analyze datasets of GxG and GxE association studies using R functions.
  • Haplotype analysis
    • Methods for haplotype reconstruction and analysis will be discussed and illustrated in a computer lab using software, such as THESIAS and FBAT.

Day 4 –May 31st
(Concurrent Sessions – lectures and computer labs - except for the first session)

Presentation of current research by a Faculty member in Genetic Epidemiology
Speaker: Guillaume Lettre
Title: The genetics of adult height in populations of European and African ancestry
Time
: 8:00 – 8:40
Place: Room 1

Advanced Concepts in Population Genomics
Instructors: Laurent Excoffier, Lluís Quintana-Murci and Luis B. Barreiro
Time: 8:45 – 17:00
Place: Room 1

  • Estimation of demographical parameters: Analysis of real data on which students will use simulation-based approaches to estimate demographical parameters.
  • Methods to detect natural selection (part II): Analysis of real data on which students will perform all different types of neutrality tests.
  • Practical examples of natural selection in humans: This lecture will critically discuss our current understanding about the role played by natural selection during human evolution.

Advanced Concepts in Genetic Epidemiology and Statistical Genetics
Instructors: Guillaume Lettre and Aurélie Labbe
Time: 8:45 – 17:00
Place: Room 2

  • Design and analysis of genome-wide association studies
    • The first part of this lecture will be interactive and will include an introduction to the PLINK software. We will review statistical methods for the association analysis of quantitative and qualitative traits. We will go over data quality control, population stratification and admixture, single locus analyses, multiple testing correction, multi-locus analyses and imputation of genotypes.
    • The second part of this lecture will consist of a computer laboratory. We will assess study design and computational challenges related to the analysis of GWAS data. To do so, students will analyze real genotypes from a GWAS data with simulated phenotypes using either R or the PLINK software.
  • Introduction to the analysis of expression quantitative trait loci (eQTL)
    • In the first part of the lecture, we will review the analysis of gene expression data and how such expressions can be seen as quantitative traits in eQTL studies. Then, we will discuss some Bayesian statistical methods that have been developed for the detection of cis- and trans- eQTLs.
    • The second part of the lecture will consist of a computer laboratory. Using a current software (in R), we will analyze a complete dataset to illustrate the methods discussed in the first part of the lecture.

Day 5 –June 1st
(Concurrent Sessions – lectures and computer labs - except for the first two and the last sessions)

Presentation of current research by a Faculty member in Population Genomics
Speaker: Lluis Quintana-Murci
Title: Natural Selection on the immune system
Time
: 8:00 – 8:40
Place: Room 1

Sources of Genetic Data (joint session)
Instructor: Guillaume Bourque
Time: 8:45 – 9:45
Place: Room 1

  • This session will describe sources of data used in genetic analyses, including SNP data and next generation sequencing data. Available databases and web resources will be presented.

Advanced Concepts in Population Genomics
Instructors: Laurent Excoffier and Luis B. Barreiro
Time: 10:15 – 14:45
Place: Room 1

  • This session will discuss different methods to :
    • identify populations tructure using genome-wide genotype data
    • estimate levels of admixture
    • extimate ancestry segments in admixed individuals.

Advanced Concepts in Genetic Epidemiology and Statistical Genetics
Instructor: Celia Greenwood
Time: 10:15 – 14:45
Place: Room 2

  • Analysis of rare variants
    • The type of data arising from resequencing studies will be described, demonstrating the analytic challenges. Several strategies for analysis based on differenct concepts (increased burden, increased variance, haplotype sharing) will be described.
    • The second lecture will be a computer laboratory, providing an opportunity to analyze real and simulated data sets using some currently available software packages such as SKAT, VT, and C-alpha.

Round Table: "What's next..."
Instructors: All Faculty and attending Scientific Committee Members
Time: 15:15 – 17:00
Place: Room 1

  • Participants will be encouraged to bring up questions and issues that they have regarding future research in the fields of population genomics and genetic epidemiology. Faculty will give their opinions and discuss with the participants on these issues.