Please see below for details of a one-day workshop (lectures plus
practical sessions) on GWAS methods by University College London
Genetics Institute.
For more information or to register, visit this link
https://www.eventbrite.com/e/ucl-short-course-understanding-the-genetic-architecture-of-complex-traits-tickets-50034528622?aff=ebdssbdestsearch
Thanks, Doug
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Description
Date: Tuesday 23rd October, University College London, 10am-4.30pm
Tutors: Prof David Balding (Melbourne and UGI) and Dr Doug Speed (Aarhus
and UGI)
Cost: £40 (or £30 for UCL Members)
Advance Registration is REQUIRED
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*
*Background: *In recent years there has been great progress in
developing genome-wide statistical analyses for detecting causal
variants, constructing prediction models and better understanding the
genetic architecture of complex traits. However the underlying
regression models involve very large numbers of predictors, and strong
modelling assumptions are required to tackle the consequent problem of
over-fitting. The results can be sensitive to these assumptions, and
also to the effects of population structure, genotyping errors and the
extent to which rare SNPs are included. Recently-developed methods based
on summary statistics are susceptible to similar problems
*Course outline: *We will cover genome-wide association analysis,
including latest developments in confounding adjustments, and
heritability analyses, both using individual-level genetic data (GCTA,
LDAK) and using summary statistics (LDSC, SumHer). We will also cover
assessing heritability enrichment in functionally-annotated regions,
genetic correlation and risk prediction (e.g., polygenic risk scores,
BLUP and MultiBLUP). We will emphasise the common elements of these
methods, highlighting a standard 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 indvidual-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 with either MAC or LINUX OS
*Prerequisites:* Participants should be proficient in statistics
including some familiarity with random-effects regression models. In
genetics, knowledge of SNP genotypes and Hardy-Weinberg and linkage
equilibrium 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*
*10:00 - 12:20: 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.
*12:20 - 13:00: Lunch*
*13.00 - 14:40: Lecture 2 followed by Practical 2*
Methods based on summary statistics, assessing the effects of
confounding in association analysis, enrichment of functional
categories. LDSC, SumHer softwares
*14:40 - 15:00: Break*
*15.00 - 16:30: Lecture 3 followed by Practical 3
*
Genetic correlations, genomic prediction and enhanced polygenic risk
scores.
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