Date: 2018-03-16

Time: 15:30-16:30

Location: BURN 1205

Abstract:

Over the last decade, advances in measurement technologies has enabled researchers to generate multiple types of high-dimensional “omics” datasets for large cohorts. These data provide an opportunity to derive a mechanistic understanding of human complex traits. However, inferring meaningful biological relationships from these data is challenging due to high-dimensionality , noise, and abundance of confounding factors. In this talk, I’ll describe statistical approaches for robust analysis of genomic data from large population studies, with a focus on 1) understanding the nature of confounding and approaches for addressing them and 2) understanding the genomic correlates of aging and dementia.

Speaker

Sara Mostafavi is an Assistant Professor at the Department of Statistics and the Department of Medical Genetics, and an affiliate member of the Department of Computer Science, at University of British Columbia (UBC).