Title: New advances in understanding complex traits through mixed model analysis

Abstract:
SNP-based Heritability Analysis has demonstrated that for most complex traits,  SNPs tend to explain the majority of heritability. However, it also tells us that most traits are highly polygenic, with 100s, if not 1000s, of variants influencing the phenotype. Fortunately, extensions of heritability analysis are providing us with dozens of new tools for investigating complex traits; whether this be aiding our search for causal loci, creating prediction models, or generally improving our understanding of their genetic architecture. I will outline some of many new methods, using examples from epilepsy, breast cancer, Parkinson's Disease as well as plant and animal datasets. 

About the speaker:
Doug Speed is a research fellow at University College London. His work focuses on developing statistical methodology for analysing genome-wide association study data. He is particularly interested in SNP-based heritability analysis, for which he has produced the software LDAK http://www.ldak.org.