A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies
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-lihoo...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2012/642403 |
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| author | Jingyuan Zhao Zehua Chen |
| author_facet | Jingyuan Zhao Zehua Chen |
| author_sort | Jingyuan Zhao |
| collection | DOAJ |
| description | 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). |
| format | Article |
| id | doaj-art-16e6dbe7d05042bbbb3797f8eca266d5 |
| institution | Kabale University |
| issn | 1687-952X 1687-9538 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Probability and Statistics |
| spelling | doaj-art-16e6dbe7d05042bbbb3797f8eca266d52025-08-20T03:54:32ZengWileyJournal of Probability and Statistics1687-952X1687-95382012-01-01201210.1155/2012/642403642403A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association StudiesJingyuan Zhao0Zehua Chen1Human Genetics, Genome Institute of Singapore, 60 Biopolis, Genome No. 02-01, 138672, SingaporeDepartment of Statistics and Applied Probability, National University of Singapore, 3 Science Drive 2, 117546, SingaporeWe 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).http://dx.doi.org/10.1155/2012/642403 |
| spellingShingle | Jingyuan Zhao Zehua Chen A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies Journal of Probability and Statistics |
| title | A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies |
| title_full | A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies |
| title_fullStr | A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies |
| title_full_unstemmed | A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies |
| title_short | A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies |
| title_sort | two stage penalized logistic regression approach to case control genome wide association studies |
| url | http://dx.doi.org/10.1155/2012/642403 |
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