Statistical Bioinformatics Seminar: Keri Multerer

Title: Polygenic risk score analysis with the addition of higher order interactions
provides insight into protective and risk components of type 2 diabetes 

Speaker: Keri Multerer (Victoria University of Wellington) 

Abstract: Polygenic risk scores (PRS) based on genome wide association studies (GWAS)
have been studied since about 2008.  The PRS concept is based on obtaining individual
DNA sequence information that is then compared for disease association using summary
statics (derived from GWAS) in public databases.  However, current PRS are not yet
robust enough to be generally used in a clinical setting for flagging high risk
individuals.  Using data available in the UK Biobank with type 2 diabetes as the disease
model, we have developed novel methods to incorporate higher order (epistatic)
interaction weights to be included in PRS.  This will help us to better understand if
and by how much higher order interactions explain individual genetic risk.  Currently we
have improved feature selection for both main effect and epistatic interactions without
sacrificing interpretability of the results leading to novel insights into the risk and
protective variants driving type 2 diabetes.  

About the speaker: Keri Multerer is a 3rd year PhD student at Victoria University of
Wellington in New Zealand under co-supervision of Andrew Munkacsi and Paul Atkinson.
She earned a MSc in Genetics from George Washington University in Washington DC and
worked in cancer research at Fred Hutchinson Cancer Research Center in Seattle before
taking time off to raise three daughters.  Teaching herself to code (in python) with
specialised machine learning courses, Keri has integrated these two passions in her PhD
thesis contributing to the fields of public health and personalised medicine.