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Reducing bias of genetic effect estimates when transforming between linear and non-linear scales
UNFORTUNATELY, THIS SEMINAR HAS BEEN POSTPONED
In Genome Wide Association Studies the relationship between a phenotype, with discrete outcome levels, and a genotype is typically assessed via linear regression, which necessarily ignores the non-normality of the outcome. Motivated by this, we consider a transformation that connects the linear effects to the non-linear scale. The approach improves on current transformations by maintaining small bias, of the non-linear genetic effect estimate, when variation in the outcome is explained mainly by additional covariates, e.g. age and gender.
As an example, we consider a binary trait and several genetic and non-genetic predictors connected via a logit link-function. The method, however, is applicable to a wide class of non-normal phenotypes and link-functions.
Date:
11 July 2016, 14:00
Venue:
Wellcome Trust Centre for Human Genetics, Headington OX3 7BN
Venue Details:
Seminar Room A
Speaker:
Dr Chris Foley (University of Cambridge)
Organising department:
Wellcome Trust Centre for Human Genetics
Organiser:
Professor Gil McVean (University of Oxford)
Organiser contact email address:
mcvean@well.ox.ac.uk
Host:
Professor Gil McVean (University of Oxford)
Part of:
WHG Seminars
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Emma Jones
