文章基本信息

标题：A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies
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作者：Jingyuan Zhao ; Zehua Chen
期刊名称：Journal of Probability and Statistics
印刷版ISSN：1687-952X
电子版ISSN：1687-9538
出版年度：2012
卷号：2012
DOI：10.1155/2012/642403
出版社：Hindawi Publishing Corporation
摘要：We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using 𝐿1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD) penalty (Fan and Li, 2001) and Jeffrey’s Prior penalty (Firth, 1993), a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008). The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS) project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005) and the LASSO-patternsearch algorithm (Shi et al. 2007).