{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T05:57:10Z","timestamp":1773295030440,"version":"3.50.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"22","license":[{"start":{"date-parts":[[2017,6,23]],"date-time":"2017-06-23T00:00:00Z","timestamp":1498176000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100007225","name":"Ministry of Science and Technology","doi-asserted-by":"publisher","award":["PH-105-PP-03"],"award-info":[{"award-number":["PH-105-PP-03"]}],"id":[{"id":"10.13039\/100007225","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004737","name":"National Health Research Institutes","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004737","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Identification of single nucleotide polymorphism (SNP) interactions is an important and challenging topic in genome-wide association studies (GWAS). Many approaches have been applied to detecting whole-genome interactions. However, these approaches to interaction analysis tend to miss causal interaction effects when the individual marginal effects are uncorrelated to trait, while their interaction effects are highly associated with the trait.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A grouped variable selection technique, called two-stage grouped sure independence screening (TS-GSIS), is developed to study interactions that may not have marginal effects. The proposed TS-GSIS is shown to be very helpful in identifying not only causal SNP effects that are uncorrelated to trait but also their corresponding SNP\u2013SNP interaction effects. The benefit of TS-GSIS are gaining detection of interaction effects by taking the joint information among the SNPs and determining the size of candidate sets in the model. Simulation studies under various scenarios are performed to compare performance of TS-GSIS and current approaches. We also apply our approach to a real rheumatoid arthritis (RA) dataset. Both the simulation and real data studies show that the TS-GSIS performs very well in detecting SNP\u2013SNP interactions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>R-package is delivered through CRAN and is available at: https:\/\/cran.r-project.org\/web\/packages\/TSGSIS\/index.html.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btx409","type":"journal-article","created":{"date-parts":[[2017,6,22]],"date-time":"2017-06-22T11:16:05Z","timestamp":1498130165000},"page":"3595-3602","source":"Crossref","is-referenced-by-count":8,"title":["TSGSIS: a high-dimensional grouped variable selection approach for detection of whole-genome SNP\u2013SNP interactions"],"prefix":"10.1093","volume":"33","author":[{"given":"Yao-Hwei","family":"Fang","sequence":"first","affiliation":[{"name":"Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan"}]},{"given":"Jie-Huei","family":"Wang","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan"}]},{"given":"Chao A","family":"Hsiung","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan"}]}],"member":"286","published-online":{"date-parts":[[2017,6,23]]},"reference":[{"key":"2023051308272940600_btx409-B1","doi-asserted-by":"crossref","first-page":"962","DOI":"10.1016\/j.ajhg.2012.04.017","article-title":"Inclusion of gene\u2013gene and gene\u2013environment interactions unlikely to dramatically improve risk prediction for complex diseases","volume":"90","author":"Aschard","year":"2012","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B2","doi-asserted-by":"crossref","first-page":"D991","DOI":"10.1093\/nar\/gks1193","article-title":"NCBI GEO: archive for functional genomics data sets-update","volume":"41","author":"Barrett","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2023051308272940600_btx409-B3","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1093\/bioinformatics\/btt633","article-title":"Testing multiple biological mediators simultaneously","volume":"30","author":"Boca","year":"2014","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B4","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1093\/genetics\/139.3.1455","article-title":"Epistasis and its contribution to genetic variance-components","volume":"139","author":"Cheverud","year":"1995","journal-title":"Genetics"},{"key":"2023051308272940600_btx409-B5","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.ajhg.2015.11.021","article-title":"An efficient multiple-testing adjustment for eQTL studies that accounts for linkage disequilibrium between variants","volume":"98","author":"Davis","year":"2016","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B6","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1214\/10-IMSCOLL606","article-title":"High-dimensional Variable Selection for Cox's Proportional Hazards Model","volume":"6","author":"Fan","year":"2010","journal-title":"Institute of Mathematical Statistics, Collections, Borrowing Strength: Theory Powering Applications-A Festschrift for Lawrence D. Brown"},{"key":"2023051308272940600_btx409-B7","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1111\/j.1467-9868.2008.00674.x","article-title":"Sure independence screening for ultrahigh dimensional feature space","volume":"70","author":"Fan","year":"2008","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol"},{"key":"2023051308272940600_btx409-B8","first-page":"2013","article-title":"Ultrahigh dimensional feature selection: beyond the linear model","volume":"10","author":"Fan","year":"2009","journal-title":"J. Mach. Learn. Res"},{"key":"2023051308272940600_btx409-B9","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1002\/gepi.21602","article-title":"SVM-based generalized multifactor dimensionality reduction approaches for detecting gene\u2013gene interactions in family studies","volume":"36","author":"Fang","year":"2012","journal-title":"Genet. Epidemiol"},{"key":"2023051308272940600_btx409-B10","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1016\/j.ajhg.2014.02.013","article-title":"Fine mapping seronegative and seropositive rheumatoid arthritis to shared and distinct hla alleles by adjusting for the effects of heterogeneity","volume":"94","author":"Han","year":"2014","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B11","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1080\/01621459.2014.881741","article-title":"Interaction screening for ultrahigh-dimensional data","volume":"109","author":"Hao","year":"2014","journal-title":"J. Am. Stat. Assoc"},{"key":"2023051308272940600_btx409-B12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/bioinformatics\/btq600","article-title":"A variable selection method for genome-wide association studies","volume":"27","author":"He","year":"2011","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B13","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s10994-014-5438-z","article-title":"Leave-one-out cross-validation is risk consistent for lasso","volume":"97","author":"Homrighausen","year":"2014","journal-title":"Mach. Learn"},{"key":"2023051308272940600_btx409-B14","doi-asserted-by":"crossref","first-page":"2797","DOI":"10.1093\/bioinformatics\/btt485","article-title":"iBMQ: a R\/Bioconductor package for integrated Bayesian modeling of eQTL data","volume":"29","author":"Imholte","year":"2013","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B15","doi-asserted-by":"crossref","first-page":"250","DOI":"10.2174\/13892029113149990001","article-title":"Gene-based genomewide association analysis: a comparison study","volume":"14","author":"Kang","year":"2013","journal-title":"Curr. Genomics"},{"key":"2023051308272940600_btx409-B16","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pgen.1000587","article-title":"Statistical estimation of correlated genome associations to a quantitative trait network","volume":"5","author":"Kim","year":"2009","journal-title":"Plos Genet"},{"key":"2023051308272940600_btx409-B17","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1038\/ejhg.2013.69","article-title":"Kernel canonical correlation analysis for assessing gene\u2013gene interactions and application to ovarian cancer","volume":"22","author":"Larson","year":"2014","journal-title":"Eur. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B18","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1038\/ejhg.2015.16","article-title":"A gene-based information gain method for detecting gene\u2013gene interactions in case\u2013control studies","volume":"23","author":"Li","year":"2015","journal-title":"Eur. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B19","doi-asserted-by":"crossref","first-page":"2292","DOI":"10.1214\/14-AOAS771","article-title":"A fast algorithm for detecting gene\u2013gene interactions in genome-wide association studies","volume":"8","author":"Li","year":"2014","journal-title":"Ann. Appl. Stat"},{"key":"2023051308272940600_btx409-B20","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.ajhg.2011.01.019","article-title":"GATES: a rapid and powerful gene-based association test using extended simes procedure","volume":"88","author":"Li","year":"2011","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B21","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1093\/bioinformatics\/btn641","article-title":"ATOM: a powerful gene-based association test by combining optimally weighted markers","volume":"25","author":"Li","year":"2009","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B22","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1002\/gepi.20610","article-title":"Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies","volume":"35","author":"Lin","year":"2011","journal-title":"Genet. Epidemiol"},{"key":"2023051308272940600_btx409-B23","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.3724\/SP.J.1005.2013.01065","article-title":"Advances on gene-based association analysis","volume":"35","author":"Luo","year":"2013","journal-title":"Hereditas (Beijing)"},{"key":"2023051308272940600_btx409-B24","doi-asserted-by":"crossref","first-page":"e1003321.","DOI":"10.1371\/journal.pgen.1003321","article-title":"Gene-based testing of interactions in association studies of quantitative traits","volume":"9","author":"Ma","year":"2013","journal-title":"Plos Genet"},{"key":"2023051308272940600_btx409-B25","first-page":"16","article-title":"Group sure independence screening for ultrahigh dimensional variable selection","volume":"30","author":"Ma","year":"2015","journal-title":"Stat. Inf. Forum"},{"key":"2023051308272940600_btx409-B26","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.ymeth.2009.03.004","article-title":"Detection and interpretation of expression quantitative trait loci (eQTL)","volume":"48","author":"Michaelson","year":"2009","journal-title":"Methods"},{"key":"2023051308272940600_btx409-B27","first-page":"708","article-title":"Gene\u2013environment and gene\u2013gene interactions in GWAS","volume":"32","author":"Murcray","year":"2008","journal-title":"Genet. Epidemiol"},{"key":"2023051308272940600_btx409-B28","doi-asserted-by":"crossref","first-page":"S69.","DOI":"10.1186\/1753-6561-1-S1-S69","article-title":"Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm","volume":"1","author":"Namkung","year":"2007","journal-title":"BMC Proceedings"},{"key":"2023051308272940600_btx409-B29","doi-asserted-by":"crossref","first-page":"S108.","DOI":"10.1186\/1753-6561-5-S9-S108","article-title":"Detection of rare functional variants using Group ISIS","volume":"5","author":"Niu","year":"2011","journal-title":"BMC Proceedings"},{"key":"2023051308272940600_btx409-B30","doi-asserted-by":"crossref","first-page":"765","DOI":"10.1086\/383251","article-title":"A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other","volume":"74","author":"Nyholt","year":"2004","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B31","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1038\/ejhg.2009.223","article-title":"A gene-based method for detecting gene\u2013gene co-association in a case-control association study","volume":"18","author":"Peng","year":"2010","journal-title":"Eur. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B32","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1086\/321276","article-title":"Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer","volume":"69","author":"Ritchie","year":"2001","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B33","doi-asserted-by":"crossref","first-page":"1752","DOI":"10.1093\/bioinformatics\/btq257","article-title":"On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data","volume":"26","author":"Schwarz","year":"2010","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B34","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1016\/j.ajhg.2015.04.012","article-title":"Accurate and fast multiple-testing correction in eQTL studies","volume":"96","author":"Sul","year":"2015","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B35","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1093\/bioinformatics\/bts051","article-title":"A gene-based test of association using canonical correlation analysis","volume":"28","author":"Tang","year":"2012","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B36","doi-asserted-by":"crossref","DOI":"10.1186\/ar4093","article-title":"Polymorphisms in peptidylarginine deiminase associate with rheumatoid arthritis in diverse Asian populations: evidence from MyEIRA study and meta-analysis","volume":"14","author":"Too","year":"2012","journal-title":"Arthritis Res. Ther"},{"key":"2023051308272940600_btx409-B37","doi-asserted-by":"crossref","DOI":"10.1186\/1471-2105-13-72","article-title":"Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis","volume":"13","author":"Ueki","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2023051308272940600_btx409-B38","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1093\/bib\/bbs024","article-title":"Machine learning approaches for the discovery of gene\u2013gene interactions in disease data","volume":"14","author":"Upstill-Goddard","year":"2013","journal-title":"Brief. Bioinf"},{"key":"2023051308272940600_btx409-B39","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.ajhg.2010.07.021","article-title":"BOOST: a fast approach to detecting gene\u2013gene interactions in genome-wide case\u2013control studies","volume":"87","author":"Wan","year":"2010","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B40","doi-asserted-by":"crossref","first-page":"2834","DOI":"10.1093\/bioinformatics\/bts531","article-title":"Interaction-based feature selection and classification for high-dimensional biological data","volume":"28","author":"Wang","year":"2012","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B41","article-title":"Investigate pathogenic mechanism of TXNDC5 in rheumatoid arthritis","volume":"8","author":"Wang","year":"2013","journal-title":"Plos One"},{"key":"2023051308272940600_btx409-B42","doi-asserted-by":"crossref","first-page":"2936","DOI":"10.1093\/bioinformatics\/btr512","article-title":"An empirical comparison of several recent epistatic interaction detection methods","volume":"27","author":"Wang","year":"2011","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B43","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.ajhg.2012.03.007","article-title":"A general framework for two-stage analysis of genome-wide association studies and its application to case\u2013control studies","volume":"90","author":"Wason","year":"2012","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B44","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1002\/gepi.20459","article-title":"Screen and clean: a tool for identifying interactions in genome-wide association studies","volume":"34","author":"Wu","year":"2010","journal-title":"Genet. Epidemiol"},{"key":"2023051308272940600_btx409-B45","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/j.ajhg.2010.05.002","article-title":"Powerful SNP-set analysis for case\u2013control genome-wide association studies","volume":"86","author":"Wu","year":"2010","journal-title":"Am. J. Hum. Genet"},{"key":"2023051308272940600_btx409-B46","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0069321","article-title":"A modified entropy-based approach for identifying gene\u2013gene interactions in case\u2013control study","volume":"8","author":"Yee","year":"2013","journal-title":"Plos One"},{"key":"2023051308272940600_btx409-B47","doi-asserted-by":"crossref","first-page":"3150","DOI":"10.1093\/bioinformatics\/btw351","article-title":"Estimating and testing high-dimensional mediation effects in epigenetic studies","volume":"32","author":"Zhang","year":"2016","journal-title":"Bioinformatics"},{"key":"2023051308272940600_btx409-B48","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.jmva.2011.08.002","article-title":"Principled sure independence screening for Cox models with ultra-high-dimensional covariates","volume":"105","author":"Zhao","year":"2012","journal-title":"J. Multivar. Anal"},{"key":"2023051308272940600_btx409-B49","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1198\/jasa.2011.tm10563","article-title":"Model-free feature screening for ultrahigh-dimensional data","volume":"106","author":"Zhu","year":"2011","journal-title":"J. Am. Stat. Assoc"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/22\/3595\/50307208\/bioinformatics_33_22_3595.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/22\/3595\/50307208\/bioinformatics_33_22_3595.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T22:47:09Z","timestamp":1750373229000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/33\/22\/3595\/3884655"}},"subtitle":[],"editor":[{"given":"Oliver","family":"Stegle","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2017,6,23]]},"references-count":49,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2017,11,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btx409","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2017,11,15]]},"published":{"date-parts":[[2017,6,23]]}}}