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Analysis of complex phenotypes in genomics

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In this talk, I will discuss some of our recent work in the area of statistical genomics, aimed at improving our biological understanding of complex phenotypes. Multiple layers of molecular phenomena are involved in the path between genes and disease. To better exploit the structure of the rich biological data that is currently being collected, statistical models of the variations within and the interplay between different layers of genomics structures are constructed. Generic Bayesian hierarchical model building ideas and algorithms have been tailored for this purpose. In this talk I will discuss three areas: refining GWAS , modelling expression data, and analysing ontology data and illustrate the modelling strategy on case studies.

This talk is part of the Statistics series.

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