Events
DMS Statistics Seminar |
| Time: Dec 01, 2017 (03:00 PM) |
| Location: Parker Hall 224 |
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Details: PLEASE NOTE CHANGE IN TIME AND LOCATION!!!!
Speaker: Li Chen, Assistant Professor of Pharmacy
Title: A sparse regression framework for integrating phylogenetic tree in predictive modeling of microbiome data
Abstract: The development of next generation sequencing offers an opportunity to predict the disease outcomes of patients using the microbiome sequencing data. Considering a typical microbiome dataset consists of more taxa than samples, and all the taxa are related to each other is the phylogenetic tree, we propose a smoothness penalty-Laplacian penalty to incorporate the prior information of phylogenetic tree to achieve coefficient smoothing in a sparse regression model. Moreover, we observe that sparsifying the Laplacian matrix usually results better prediction performance; however, the optimal threshold for sparsifying varies dataset by dataset and is unknown in real data analysis. To overcome this limitation, we further develop another phylogeny-constraint penalty based on evolutionary theory to smooth the coefficients with respect to the phylogenetic tree. Using simulated and real datasets, we demonstrate that the proposed methods has better prediction performance than the other competing methods.
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