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Activity Number: 300 - Gene-Gene and Gene-Environment Interactions
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #324322
Title: Sparse Penalization for Non-Hierarchical Interactions
Author(s): Claus Ekstrom*
Companies: Biostatistics, University of Copenhagen
Keywords: penalization ; genetics ; lasso ; interactions
Abstract:

Penalized regression methods such as the lasso and the elastic net have proven useful in high-dimensional setting such as genome-wide association studies where a large number of predictors are analyzed simultaneously and sparsity is common. Sparse non-hierarchical interaction models are of special interest in these settings since gene-gene and gene-environment interactions may well give rise to these non-hierarchical interactions.

In the talk we discuss the interaction situations that arise in genetic studies, and present a penalization approach to accommodate these special, structured situations. We compare the performance to results obtained from alternative penalization approaches such as two-step inclusion procedures, overlap group lasso, or deliberately misspecifying the model. Finally, we apply the proposed method to a large-scale genetic dataset of type-2 related diabetes.


Authors who are presenting talks have a * after their name.

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