AIAS Short Course - Methods for Analysing Complex Trait GWAS Data
Methods for analysing complex trait genome-wide association study (GWAS) dataDate: Monday 28th October 2019, 9.30-3.30pmLocation: AIAS, Aarhus University, DENMARKTutors: Dr Doug Speed and Professor David BaldingCost: Free, but advance Registration is REQUIRED
Note that we are also providing the same course in London on Wednesday 23rd October.Background:In recent years, there has been a massive increase in the amount of genetic data available; with resources such as the UK and China-Kadoorie Biobanks, researchers can now access data for thousands of phenotypes and hundreds of thousands of individuals. There has also been great progress developing genome-wide statistical tools for detecting causal variants, constructing prediction models and better understanding the genetic architecture of complex traits.Course outline:We will cover a wide range of GWAS analyses. We will begin with basic analyses, such as quality control, single-SNP regression and classical polygenic risk scores. However, the main focus will be more advanced analysis. These will include both methods that use individual-level data (e.g., mixed-model association analysis, G-REML, gene-based association tests, using tools such as Bolt-LMM, GCTA and LDAK), and methods that use summary statistics (e.g., heritability and genetic correlation analyses, using tools such as LDSC and SumHer). We will explain the principals underlying these methods, highlighting both their common elements and differences in underlying modelling assumptions.The course will compose of two lectures and two practicals. 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 a selection of worked examples; to take part in the practicals, participants should bring a laptop (ideally running either MAC or LINUX).Prerequisites:This course is designed for researchers who have at least some experience of GWAS. Participants should have a basic understanding of statistics, and would ideally be familiar with the idea of a shrinkage regression. Knowledge of SNP genotypes and linkage disequilibrium will be assumed. Computer scripts and output will be discussed that assume some familiarity with scientific computing using Linux. Experience with PLINK would be helpful but is not essential.
Provisional Timetable:09:30 - 12:00: Lecture 1 followed by Practical 1Introduction to analysing GWAS data, including quality control, single-SNP analysis, polygenic risk scores, mixed-model analysis and gene-based analysis12:00 - 13:00: Lunch break - participants can bring a lunchbox, or purchase food at the cafe next door13:00 - 15.30: Lecture 2 followed by Practical 2Estimating heritability, confounding bias, bivariate correlations and enrichment of functional categoriesTea, coffee, juice and biscuits will be provided throughout the day
Notes:If travelling from abroad, the closest airports are Aarhus and Billund (45 and 75 minutes away)
Any questions, email doug "at" aias.au.dk