Title: "Two-Stage Penalized Least Squares Method to Construct Large Gene Regulatory Networ ks"
Speaker: Chen Chen, Department of Staistics, Purdue University

Place: LILLY Hall G126
Date: October 6, 2015; Tuesday
Time: 4:30pm

Constructing whole-genome gene regulatory networks using genetical genomics data is challenged by limited computer memory and intensive computation. In this talk, I will present a two-stage penalized least squares method to study regulatory interactions among massive genes, building up reciprocal graphical models on the basis of simultaneous equation models. Fitting a single regression model for each gene at each stage, the method employs the L2 penalty at the first stage to obtain consistent estimation of surrogate variables, and the L1 penalty at the second stage to consistently select regulatory genes among massive candidates. I will show that the resultant estimates of the regulatory effects enjoy the oracle properties. Without fitting a full information model, the method is computationally fast and also allows for parallel implementation. We demonstrated the effectiveness of the method by conducting simulation studies, showing its improvements over other methods. Our method was also applied to construct a yeast gene regulatory network.

Associated reading:
Jansen and Nap. 2001.Genetical genomics: the added value from segregation. Trends in Genetics. 17(7):388-391.

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