Laboratory

Design and Analysis of Genetic-based Association Studies

26–30 September 2016

Wellcome Genome Campus, Hinxton, UK

Summary

This advanced course aims to give researchers involved in genetic disease
studies a firm grounding in the use of the latest statistical methods and
software for analysis of genetic association studies. This includes both
small-scale disease-specific studies and large-scale collaborative
projects including those that can be used for analysis of multiple
complex traits such as UK Biobank.

The course will cover both theoretical and practical aspects of the
design and analysis of such studies. Each topic will include a lecture
followed by a practical session in which state-of-the-art statistical
software will be applied to relevant datasets. The practical sessions
will illustrate the ideas presented in the lectures. All the software
used will be freely available so that skills learned can be applied after
the course.

Learning outcomes
On completion of the course, participants can expect to:

  • Understand the general principles, assumptions and basic techniques used in genetic association studies
  • Read and comprehend scientific articles that present results from candidate-gene and genome-wide association studies
  • Analyse genetic data arising from candidate-gene and genome-wide association studies, (including quality control checks and association between genotype and phenotype)
  • Perform imputation of variants that have not been directly genotyped, using information from genotyped genetic variants

Please note: To ensure participants benefit fully from
the course, applications should include clear evidence of the following
existing knowledge and experience:

  • a strong quantitative background (including some familiarity with statistics, mathematics or bioinformatics)
  • a reasonable level of computer literacy and should currently be engaged in relevant research.
  • a basic knowledge and understanding of genetics (both molecular genetics and concepts of inheritance/heritability)

Feedback from the 2015 course

“I would like to thank the instructors and organisation for this
wonderful course. I’ve learned a lot in this course, this will definitely
helps me in my further analysis.”

“Many thanks for all the hard work that went into organising the course.
It was a great experience in every aspect. The instructors couldn’t have
been better!”

“I really enjoyed the course not only for acquired knowledge but also for
the kindness and superb accommodation. But I especially liked interacting
with skilled people from prestigious institutions around the world.”

“I would like to thank all wonderful instructors of the course and their
assistants to provide such a great opportunity to learn/practice
genetic-based association studies. Also I would appreciate the course
organising team for their great support! Thank you all. you are amazing!”

“I just would like to say that this course will definitely improve a lot
the way I perform data analysis. It was a great opportunity to learn new
methods and also to ask questions and discuss my research with real
specialists. Brilliant team!”

Programme

The programme will include lecture and computer-based practical sessions
covering the following topics:

Introduction to genetic association studies
Overview and history of genetic association studies leading up to and
including genome-wide association studies.

Basic association analysis and meta-analysis
Single marker association tests (frequentist and Bayesian approaches).
Calculation of odds ratios and relative risks. Logistic regression.
Meta-analysis (fixed-effects and trans-ethnic). Tests of gene-environment
and gene-gene interaction.

Quality control and population structure
Data quality control procedures to avoid the generation of spurious false
positives in association studies. The confounding effects of population
structure on association studies and methods for protecting against these
effects. PCA and mixed model approaches.

Haplotype estimation and genotype imputation
Methods for genotype imputation using publicly available reference
panels. Pre-phasing of haplotypes and imputation based on these inferred
haplotypes. Frequentist and Bayesian methods of testing association at
imputed SNPs and indels. Quality control for imputed SNPs. Meta-analysis
using imputed data.

Heritability and mixed models
Concepts of heritability and “missing heritability”. Use of linear mixed
modelling approaches to partition heritability and to adjust for
population substructure and relatedness in genome-wide association
studies.

Analysis of rare variants
Methods for analysing rare variants from re-sequencing, genotyping and
imputation studies via “collapsing approaches”.

Family-based association studies
Testing for association using family-based study designs. Comparison with
designs that use unrelated individuals.

Practical Sessions
Lectures are followed by practical sessions using realistic datasets so
that students learn how to apply the theory. Students will use a variety
of computer programs during the course including: IMPUTE2, SHAPEIT2,
SNPTEST2, QCTOOL, META, GRANVIL, GCTA, FaST-LMM, CASSI, PLINK.

The programme will also include seminars from internationally renowned
researchers from the field of complex disease genetics, along with
opportunities for participants to discuss their own research projects
with course instructors and with each other.

Learning Outcomes
On completion of the course, participants can expect to:

  • Understand the general principles, assumptions and basic techniques used in genetic association studies
  • Read and comprehend scientific articles that present results from candidate-gene and genome-wide association studies
  • Analyse genetic data arising from candidate-gene and genome-wide association studies, (including quality control checks and association between genotype and phenotype)
  • Perform imputation of variants that have not been directly genotyped, using information from genotyped genetic variants

Instructors and speakers

Course instructors
Heather Cordell Institute of Genetic Medicine, Newcastle University, UK
Andrew Morris University of Liverpool, UK
Jonathan Marchini Department of Statistics, University of Oxford, UK

Guest speakers
Cecilia Lindgren University of Oxford, UK
Louise Wain University of Leicester, UK

How to apply

Prerequisites
Applicants should have:

  • a strong quantitative background (including some familiarity with statistics, mathematics or bioinformatics)
  • a reasonable level of computer literacy and should currently be engaged in relevant research.
  • a basic knowledge and understanding of genetics (both molecular genetics and concepts of inheritance/heritability).

Cost
The
course is subsidised by the Wellcome Genome Campus
Advanced Courses and Scientific Conferences Programme. This is a
residential
course and there is a fee of £745 towards board and lodging
for non-commercial applicants. Please contact us for the commercial fee.

Applications
Applications for this course can be completed online. If you have any
problems with the online application process, please contact us.

Please note: Applications
must be supported by a
recommendation from a scientific or clinical sponsor (e.g. supervisor or
head of department). A request for a supporting
statement will be sent
to your nominated sponsor automatically during
the application process.
Applicants must ensure that their sponsor
provides this supporting
statement by the application deadline. Applications without a supporting
statement cannot be considered.

Deadlines
Deadline for Applications: Closed

 

Cost

Bursaries
Courses are subsidised for non-commercial applicants
from anywhere in the world. Additional, limited bursaries are
available
(up to 50% of the course fee) and are awarded on merit. If you would like
to apply for a
bursary, please complete the bursary section of the
online application
form.

Please note that both the applicant
and sponsor are required to provide
a justification for the
bursary as part of the application.

Bursary terms and conditions

UK Courses (held at the Wellcome Genome Campus, Hinxton,
Cambridge)
A
limited number of bursaries are available for each course. These are
awarded by the selection committee according to merit. The bursary
covers a maximum of 50% of the course fee, though in exceptional
circumstances an application for the total course fee may be considered.
Where there are many bursary applications, the selection committee may
issue smaller amounts. We cannot assist with travel costs to attend UK
courses.

Overseas Courses (held outside of the UK)
A
limited number of bursaries are available for each course. These are
awarded on merit to cover travel, accommodation and sustenance. The
maximum award for travel (economy class) will be £750.

Bursaries can be applied for as part of the course application form.
Applicants
will be notified of a bursary award along with their place on
the
course, usually within one month of the application deadline. The
decision of the selection committee is
final.

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