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Association mapping and prediction of complex structured phenotypes

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If you have a question about this talk, please contact Emli-Mari Nel.

The goal of genetic association studies is to relate polymorphic genetic loci with quantitative traits that capture phenotypic variation.This task is well studied for a univariate or multiple independent trait variables. However, modern high-dimensional phentoypes often exhibit structure, which needs to be accounted for. In this talk I will discuss learning techniques that explicitly address this structure and allow for improved mapping and prediction of such phenotypic traits.

The discussion includes methods to account for confounding factors and phenotypes that are recorded as a time series. Applications include the prediction of the depression state of patients over the course of a treatment.

This talk is part of the Inference Group series.

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