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SUMMARY:&quot\;Genomic prediction of complex human traits: relatedness\, t
 rait architecture and predictive meta-models&quot\; - Dr Athina Spiliopoul
 ou University of Edinburgh
DTSTART:20160202T143000Z
DTEND:20160202T153000Z
UID:TALK63426@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Abstract: Genome-wide association studies (GWAS) have identifi
 ed thousands of genomic variants that are significantly associated with co
 mplex phenotypic traits. Yet\, for most complex traits\, the translation o
 f GWAS findings into personalised medicine applications remains limited\, 
 as the accuracy achieved by genomic prediction models is usually inadequat
 e for clinical practice. In this talk\, I will describe our work on genomi
 c prediction of complex traits\, where we empirically compared several wid
 ely used prediction models\, including Ridge Regression and LASSO estimate
 d from cohort data\, and polygenic risk scores based on summary statistics
  from large meta-analyses of GWAS. I will discuss how prediction accuracy 
 changes with respect to relatedness in the study cohorts and genetic archi
 tecture of the trait\, and show how we can combine genomic predictors to i
 ncrease accuracy. I will conclude with what I think are promising directio
 ns for future research in the area of genomic prediction.
LOCATION:Large  Seminar Room\, 1st Floor\, Institute of Public Health\, Un
 iversity Forvie Site\, Robinson Way\, Cambridge
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