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Statistics Faculty Research and Publications

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Package ‘springer’

Zhou, Fei; Liu, Yuwen; Lu, Xi; Ren, Jie; Wu, Cen (2023-09-19)

Recently, regularized variable selection has emerged as a powerful tool to iden- tify and dissect gene-environment interactions. Nevertheless, in longitudinal studies with high di- mensional genetic factors, regularization ...
Package ‘regnet’

Ren, Jie; Jung, Luann C.; Du, Yinhao; Wu, Cen; Jiang, Yu; Liu, Junhao (2022-08-18)

Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of ...
Supporting Information for “Robust Bayesian variable selection for gene-environment interactions”

Ren, Jie; Zhou, Fei; Li, Xiaoxi; Ma, Shuangge; Jiang, Yu; Wu, Cen (2022)
Identification of Prognostic Genes and Pathways in Lung Adenocarcinoma Using a Bayesian Approach

Jiang, Yu; Huang, Yuan; Du, Yinhao; Zhao, Yinjun; Ren, Jie; Ma, Shuangge; Wu, Cen (2017)

Lung cancer is the leading cause of cancer-associated mortality in the United States and the world. Adenocarcinoma, the most common subtype of lung cancer, is generally diagnosed at the late stage with poor prognosis. In ...
Package ‘spinBayes’

Ren, Jie; Zhou, Fei; Li, Xiaoxi; Wu, Cen; Jiang, Yu (2020-06-22)

Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Existing Bayesian methods for gene-environment (G×E) ...