Methods and Software for Analysing Complex Trait GWAS Data

Methods and Software for Analysing Complex Trait GWAS Data

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£90

Date and time

Location

Paris Research Center Cardiovascular - Inserm University Paris City

56 Rue Leblanc

75015 Paris

France

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Refunds up to 7 days before event

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Genome-wide association, heritability and prediction analysis methods. Practical sessions will introduce and use the LDAK software.

About this event

Course Leaders

David Balding, Melbourne Integrative Genomics, University of Melbourne , Australia, and UCL Genetics Institute, London.

Doug Speed, Center for Quantitative Genetics and Genomics, Aarhus University, Denmark.

Cost

GBP 90, which is currently about EUR 105. This includes lunch, refreshments and Eventbrite fees.

Course outline

This workshop will cover genome-wide association analysis, including latest developments in heritability analyses, both using individual-level genetic data (e.g. GCTA and LDAK software) and using summary statistics (LDSC, SumHer). The workshop will also cover assessing heritability enrichment in functionally-annotated regions, genetic correlation and risk prediction (polygenic risk scores, BLUP and MultiBLUP). The common elements of these methods will be emphasised, highlighting a modelling framework that has emerged for genome-wide SNP analysis, while also contrasting the differences in modelling assumptions underlying the different software.

The practicals will provide step-by-step details for analysing genetic data, starting either with individual-level data (e.g. PLINK files or the output from IMPUTE2) or summary statistics (p-values from a GWAS). There will be worked examples; to take part in the practicals, participants should bring a laptop computer with a recent version of R installed. LDAK and other scientific software require the Linux Operating System, which is available under MAC OS using Terminal.app, and under Windows 10 or later using Windows Subsystem for Linux (WSL), see https://docs.microsoft.com/en-us/windows/wsl/install

Prerequisites

Participants should be proficient in statistics including maximum-likelihood estimation and hypothesis testing, preferably some familiarity with random-effects regression models and experience of computer-based data analysis. In genetics, knowledge of SNP genotyping and Hardy-Weinberg and linkage equilibria will be assumed. Computer scripts and output will be discussed that assume some familiarity with scientific computing using Linux. Some familiarity with PLINK would be helpful but is not essential.

Provisional Timetable

9:30 - 10:00 Coffee, snack and registration.

10:00 - 12:30: Lecture 1 followed by Practical 1

Introduction to analysing GWAS data analysis using individual genotype data, kinship and heritability, both classical and SNP-based. Effect of LD, MAF and genotyping quality on heritability. GCTA and LDAK software. Methods based on summary statistics, enrichment of functional categories. LDSC, SumHer software.

12:30 - 13:30: Lunch (a light lunch will be provided)

13.30 - 16:00: Lecture 2 followed by Practical 2

The effects of confounding in association analysis. Genetic correlations. Genomic prediction using enhanced polygenic risk scores.

16:00 - 16:30 Optional wrap up session. The course leaders will be available for informal Q&A.

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