{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T16:34:13Z","timestamp":1778690053188,"version":"3.51.4"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries.<\/jats:p><jats:p>Results: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients.<\/jats:p><jats:p>Availability and implementation: The related source code and documents are freely available at https:\/\/sites.google.com\/site\/bestumich\/issues.<\/jats:p><jats:p>Contact: \u00a0yili@umich.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv517","type":"journal-article","created":{"date-parts":[[2015,9,18]],"date-time":"2015-09-18T08:26:51Z","timestamp":1442564811000},"page":"50-57","source":"Crossref","is-referenced-by-count":29,"title":["Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates"],"prefix":"10.1093","volume":"32","author":[{"given":"Kevin","family":"He","sequence":"first","affiliation":[{"name":"1 Department of Biostatistics and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanming","family":"Li","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ji","family":"Zhu","sequence":"additional","affiliation":[{"name":"2 Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongliang","family":"Liu","sequence":"additional","affiliation":[{"name":"3 Department of Medicine, Duke University School of Medicine and Duke Cancer Institute, Duke University Medical Center, Durham, NC 27710, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey E.","family":"Lee","sequence":"additional","affiliation":[{"name":"4 Department of Surgical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher I.","family":"Amos","sequence":"additional","affiliation":[{"name":"5 Department of Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, NH 03750, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Terry","family":"Hyslop","sequence":"additional","affiliation":[{"name":"6 Department of Biostatistics and Bioinformatics, Duke University and Duke Clinical Research Institute, Durham, NC 27710, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiashun","family":"Jin","sequence":"additional","affiliation":[{"name":"7 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213, USA and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huazhen","family":"Lin","sequence":"additional","affiliation":[{"name":"8 Center of Statistical Research, School of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan 611130, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qinyi","family":"Wei","sequence":"additional","affiliation":[{"name":"3 Department of Medicine, Duke University School of Medicine and Duke Cancer Institute, Duke University Medical Center, Durham, NC 27710, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2015,9,17]]},"reference":[{"key":"2023020110234186300_btv517-B100","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1002\/gepi.20623","article-title":"Stability selection for genome-wide association","volume":"35","author":"Alexande","year":"2011","journal-title":"Genetic Epidemiology"},{"key":"2023020110234186300_btv517-B1","doi-asserted-by":"crossref","first-page":"6199","DOI":"10.1200\/JCO.2009.23.4799","article-title":"Final version of 2009 AJCC melanoma staging and classification","volume":"27","author":"Balch","year":"2009","journal-title":"J. Clin. Oncol."},{"key":"2023020110234186300_btv517-B2","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"2023020110234186300_btv517-B3","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural Networks for Pattern Recognition","author":"Bishop","year":"1995"},{"key":"2023020110234186300_btv517-B4","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1145\/130385.130401","article-title":"A training algorithm for optimal margin classifiers","volume-title":"Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory","author":"Boser","year":"1992"},{"key":"2023020110234186300_btv517-B5","volume-title":"Classification and Regression Trees","author":"Breiman","year":"1984"},{"key":"2023020110234186300_btv517-B6","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"2023020110234186300_btv517-B7","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-20192-9","volume-title":"Statistics for High-Dimensional Data: Methods, Theory and Applications","author":"B\u00fchlmann","year":"2011"},{"key":"2023020110234186300_btv517-B8","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1198\/016214503000125","article-title":"Boosting with the L2 loss: regression and classification","volume":"98","author":"B\u00fchlmann","year":"2003","journal-title":"J. Am. Stat. Assoc."},{"key":"2023020110234186300_btv517-B9","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1214\/009053606000000092","article-title":"Boosting for high-dimensional linear models","volume":"34","author":"B\u00fchlmann","year":"2006","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B10","first-page":"477","article-title":"Boosting algorithms: regularization, prediction and model fitting","volume":"22","author":"B\u00fchlmann","year":"2007","journal-title":"Stat. Sci."},{"key":"2023020110234186300_btv517-B11","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1214\/009053604000000067","article-title":"Least angle regression","volume":"32","author":"Efron","year":"2004","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B12","first-page":"1","article-title":"Microarrays, empirical Bayes and the two groups model","volume":"23","author":"Efron","year":"2008","journal-title":"Stat. Sci."},{"key":"2023020110234186300_btv517-B13","volume-title":"Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction","author":"Efron","year":"2012"},{"key":"2023020110234186300_btv517-B15","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1198\/016214501753382273","article-title":"Variable selection via nonconcave penalized likelihood and its oracle properties","volume":"96","author":"Fan","year":"2001","journal-title":"J. Am. Stat. Assoc."},{"key":"2023020110234186300_btv517-B16","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1214\/aos\/1015362185","article-title":"Variable selection for Cox\u2019s proportional hazards model and frailty model","volume":"30","author":"Fan","year":"2002","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B17","article-title":"Experiments with a new boosting algorithm","author":"Freund","year":"1996"},{"key":"2023020110234186300_btv517-B18","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1214\/aos\/1016218223","article-title":"Additive logistic regression: a statistical view of boosting (with discussion)","volume":"28","author":"Friedman","year":"2000","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B19","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy function approximation: a gradient boosting machine","volume":"29","author":"Friedman","year":"2001","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B101","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1002\/bimj.200900028","article-title":"L1 penalized estimation in the Cox proportional hazards model","volume":"52","author":"Geoman","year":"2010","journal-title":"Biometrical Journal"},{"key":"2023020110234186300_btv517-B20","doi-asserted-by":"crossref","first-page":"3001","DOI":"10.1093\/bioinformatics\/bti422","article-title":"Penalized cox regression analysis in the high-dimensional and low-sample size settings with application to microarray gene expression data","volume":"21","author":"Gui","year":"2005","journal-title":"Bioinformatics"},{"key":"2023020110234186300_btv517-B102","volume-title":"Generalized Additive Models","author":"Hastie","year":"1990"},{"key":"2023020110234186300_btv517-B21","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"Hastie","year":"2009"},{"key":"2023020110234186300_btv517-B22","first-page":"453","article-title":"DNA repair: exploiting the Fanconi Anemia Pathway as a potential therapeutic target","volume":"60","author":"Hucl","year":"2010","journal-title":"Physiol. Res."},{"key":"2023020110234186300_btv517-B23","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1198\/0003130042836","article-title":"A tutorial on MM algorithms","volume":"58","author":"Hunter","year":"2004","journal-title":"Am. Stat."},{"key":"2023020110234186300_btv517-B24","doi-asserted-by":"crossref","DOI":"10.1155\/2012\/481583","article-title":"Targeting the Fanconi Anemia Pathway to identify tailored anticancer therapeutics","author":"Jenkins","year":"2012","journal-title":"Anemia"},{"key":"2023020110234186300_btv517-B25","doi-asserted-by":"crossref","first-page":"2139","DOI":"10.1038\/jid.2011.181","article-title":"Upregulation of Fanconi anemia DNA repair genes in melanoma compared with non-melanoma skin cancer","volume":"131","author":"Kao","year":"2011","journal-title":"J. Investig. Dermatol."},{"key":"2023020110234186300_btv517-B26","article-title":"Optimization","volume-title":"Springer Texts in Statistics","author":"Lange","year":"2013","edition":"2nd edn"},{"key":"2023020110234186300_btv517-B27","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1093\/bioinformatics\/bti324","article-title":"Boosting proportional hazards models using smoothing splines, with applications to high-dimensional microarray data","volume":"21","author":"Li","year":"2005","journal-title":"Bioinformatics"},{"key":"2023020110234186300_btv517-B28","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1097\/CMR.0b013e32834fc46b","article-title":"Influence of single nucleotide polymorphisms in the MMP1 promoter region on cutaneous melanoma progression","volume":"22","author":"Liu","year":"2012","journal-title":"Melanoma Res."},{"key":"2023020110234186300_btv517-B29","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1111\/j.1467-9868.2010.00740.x","article-title":"Stability selection (with discussion)","volume":"72","author":"Meinshausen","year":"2010","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"2023020110234186300_btv517-B30","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1086\/519795","article-title":"PLINK: a toolset for whole-genome association and population-based linkage analysis","volume":"81","author":"Purcell","year":"2007","journal-title":"Am. J. Hum. Genet."},{"key":"2023020110234186300_btv517-B31","doi-asserted-by":"crossref","DOI":"10.1186\/1479-5876-11-279","article-title":"Melanoma risk loci as determinants of melanoma recurrence and survival","volume":"11","author":"Rendleman","year":"2013","journal-title":"J. Transl. Med."},{"key":"2023020110234186300_btv517-B32","first-page":"172","article-title":"The state of boosting","volume":"31","author":"Ridgeway","year":"1999","journal-title":"Comput. Sci. Stat."},{"key":"2023020110234186300_btv517-B33","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.1158\/1535-7163.MCT-10-0901","article-title":"Melanoma prognosis: a REMARK-based systematic review and bioinformatic analysis of immunohistochemical and gene microarray studies","volume":"10","author":"Schramm","year":"2011","journal-title":"Mol. Cancer Therap."},{"key":"2023020110234186300_btv517-B34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v039.i05","article-title":"Regularization paths for Cox\u2019s proportional hazards model via coordinate descent","volume":"39","author":"Simon","year":"2011","journal-title":"J. Stat. Softw."},{"key":"2023020110234186300_btv517-B35","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1214\/aos\/1074290335","article-title":"The positive false discovery rate: a Bayesian interpretation and the q-value","volume":"31","author":"Storey","year":"2003","journal-title":"Ann. Stat."},{"key":"2023020110234186300_btv517-B104","doi-asserted-by":"crossref","first-page":"e1002894","DOI":"10.1371\/journal.pgen.1002894","article-title":"Exome sequencing identifies rare deleterious mutations in DNA repair genes FANCC and BLM as potential breast cancer susceptibility alleles","volume":"8","author":"Thompson","year":"2012","journal-title":"PLOS Genet."},{"key":"2023020110234186300_btv517-B36","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J. R. Stat. Soc. Ser. B (Methodological)"},{"key":"2023020110234186300_btv517-B37","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1002\/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3","article-title":"The lasso method for variable selection in the Cox model","volume":"16","author":"Tibshirani","year":"1997","journal-title":"Stat. Med."},{"key":"2023020110234186300_btv517-B38","doi-asserted-by":"crossref","first-page":"5116","DOI":"10.1073\/pnas.091062498","article-title":"Significance analysis of microarrays applied to the ionizing radiation response","volume":"98","author":"Tusher","year":"2001","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023020110234186300_btv517-B39","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1038\/jid.2014.416","article-title":"Genetic variants in Fanconi Anemia pathway genes BRCA2 and FANCA predict Melanoma survival","volume":"135","author":"Yin","year":"2015","journal-title":"J. Investig. Dermatol"},{"key":"2023020110234186300_btv517-B40","author":"Zhao","year":"2010"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/1\/50\/49016320\/bioinformatics_32_1_50.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/1\/50\/49016320\/bioinformatics_32_1_50.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T05:57:34Z","timestamp":1718085454000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/1\/50\/1742715"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,17]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btv517","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,1,1]]},"published":{"date-parts":[[2015,9,17]]}}}