{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:26:20Z","timestamp":1773275180034,"version":"3.50.1"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2315,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,6,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene\u2013gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for epistasis detection in the genome-wide scale because of the intensive computational burden. Existing epistasis detection algorithms are designed for dataset consisting of homozygous markers and small sample size. In human study, however, the genotype may be heterozygous, and number of individuals can be up to thousands. Thus, existing methods are not readily applicable to human datasets. In this article, we propose an efficient algorithm, TEAM, which significantly speeds up epistasis detection for human GWAS. Our algorithm is exhaustive, i.e. it does not ignore any epistatic interaction. Utilizing the minimum spanning tree structure, the algorithm incrementally updates the contingency tables for epistatic tests without scanning all individuals. Our algorithm has broader applicability and is more efficient than existing methods for large sample study. It supports any statistical test that is based on contingency tables, and enables both family-wise error rate and false discovery rate controlling. Extensive experiments show that our algorithm only needs to examine a small portion of the individuals to update the contingency tables, and it achieves at least an order of magnitude speed up over the brute force approach.<\/jats:p>\n               <jats:p>Contact: \u00a0xiang@cs.unc.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq186","type":"journal-article","created":{"date-parts":[[2010,6,7]],"date-time":"2010-06-07T07:28:13Z","timestamp":1275895693000},"page":"i217-i227","source":"Crossref","is-referenced-by-count":143,"title":["TEAM: efficient two-locus epistasis tests in human genome-wide association study"],"prefix":"10.1093","volume":"26","author":[{"given":"Xiang","family":"Zhang","sequence":"first","affiliation":[{"name":"1 Department of Computer Science and 2 Department of Biostatistics, University of North Carolina at Chapel Hill"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunping","family":"Huang","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and 2 Department of Biostatistics, University of North Carolina at Chapel Hill"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Zou","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and 2 Department of Biostatistics, University of North Carolina at Chapel Hill"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"1 Department of Computer Science and 2 Department of Biostatistics, University of North Carolina at Chapel Hill"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,6,1]]},"reference":[{"key":"2023012508051282800_B1","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1038\/nrg1916","article-title":"A tutorial on statistical methods for population association studies","volume":"7","author":"Balding","year":"2006","journal-title":"Nat. Rev. Genet."},{"key":"2023012508051282800_B2","doi-asserted-by":"crossref","first-page":"2003","DOI":"10.1093\/genetics\/155.4.2003","article-title":"The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci","volume":"155","author":"Carlborg","year":"2000","journal-title":"Genetics"},{"key":"2023012508051282800_B3","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1093\/genetics\/138.3.963","article-title":"Empirical threshold values for quantitative trait mapping","volume":"138","author":"Churchill","year":"1994","journal-title":"Genetics"},{"key":"2023012508051282800_B4","volume-title":"Introduction to Algorithms.","author":"Cormen","year":"2001"},{"key":"2023012508051282800_B5","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-49317-6","volume-title":"Multiple Testing Procedures with Applications to Genomics.","author":"Dudoit","year":"2008"},{"key":"2023012508051282800_B6","volume-title":"State-of-the-art algorithms for minimum spanning trees: a tutorial discussion.","author":"Eisner","year":"1997"},{"key":"2023012508051282800_B7","doi-asserted-by":"crossref","first-page":"e157","DOI":"10.1371\/journal.pgen.0020157","article-title":"Two-stage two-locus models in genome-wide association","volume":"2","author":"Evans","year":"2006","journal-title":"PLoS Genet."},{"key":"2023012508051282800_B8","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/MAHC.1985.10011","article-title":"On the history of the minimum spanning tree problem","volume":"7","author":"Graham","year":"1985","journal-title":"Ann. History Comput."},{"key":"2023012508051282800_B9","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1038\/nrg1521","article-title":"Genome-wide association studies for common diseases and complex traits","volume":"6","author":"Hirschhorn","year":"2005","journal-title":"Nat. Rev. Genet."},{"key":"2023012508051282800_B10","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1038\/nrg1155","article-title":"Mathematical multi-locus approaches to localizing complex human trait genes","volume":"4","author":"Hoh","year":"2003","journal-title":"Nat. Rev. Genet."},{"key":"2023012508051282800_B11","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1046\/j.1469-1809.2000.6450413.x","article-title":"Selecting snps in two-stage analysis of disease association data: a model-free approach","volume":"64","author":"Hoh","year":"2000","journal-title":"Ann. Hum. Genet."},{"key":"2023012508051282800_B12","first-page":"458","article-title":"The evolutionary dynamics of complex polymorphisms","volume":"14","author":"Lewontin","year":"1960","journal-title":"Evolution"},{"key":"2023012508051282800_B13","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4613-8122-8","volume-title":"Simultaneous Statistical Inference.","author":"Miller","year":"1981"},{"key":"2023012508051282800_B14","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1159\/000099179","article-title":"Detection of gene x gene interactions in genome-wide association studies of human population data","volume":"63","author":"Musani","year":"2007","journal-title":"Hum. Hered."},{"key":"2023012508051282800_B15","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1101\/gr.172901","article-title":"A combinatorial partitioning method to identify multilocus genotypic partitions that predict quantitative trait variation","volume":"11","author":"Nelson","year":"2001","journal-title":"Genome Res."},{"key":"2023012508051282800_B16","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":"2023012508051282800_B17","article-title":"Inferring missing genotypes in large snp panels using fast nearest-neighbor searches over sliding windows","author":"Roberts","year":"2007","journal-title":"Proceeding of ISMB."},{"key":"2023012508051282800_B18","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1126\/science.1142358","article-title":"Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels","volume":"316","author":"Saxena","year":"2007","journal-title":"Science"},{"key":"2023012508051282800_B19","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1371\/journal.pgen.0030115","article-title":"Genome-wide association scan shows genetic variants in the fto gene are associated with obesity-related traits","volume":"3","author":"Scuteri","year":"2007","journal-title":"PLoS Genet."},{"key":"2023012508051282800_B20","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1038\/nature05911","article-title":"Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls","volume":"447","author":"The Wellcome Trust Case Control Consortium","year":"2007","journal-title":"Nature"},{"key":"2023012508051282800_B21","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1038\/ng1666","article-title":"Genetic variation in laboratory mice","volume":"37","author":"Wade","year":"2005","journal-title":"Nat. Genet."},{"key":"2023012508051282800_B22","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1038\/ng2121","article-title":"A common variant of hmga2 is associated with adult and childhood height in the general population","volume":"39","author":"Weedon","year":"2007","journal-title":"Nat. Genet."},{"key":"2023012508051282800_B23","volume-title":"Resampling-based Multiple Testing.","author":"Westfall","year":"1993"},{"key":"2023012508051282800_B24","doi-asserted-by":"crossref","first-page":"2581","DOI":"10.1093\/bioinformatics\/btm386","article-title":"Simulating association studies: a data-based resampling method for candidate regions or whole genome scans","volume":"23","author":"Wright","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012508051282800_B25","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1093\/bioinformatics\/btn652","article-title":"SNPHarvester: a filtering-based approach for detecting epistatic interactions in genomewide association studies","volume":"25","author":"Yang","year":"2009","journal-title":"Bioinformatics"},{"key":"2023012508051282800_B26","article-title":"FastANOVA: an efficient algorithm for genome-wide association study","author":"Zhang","year":"2008","journal-title":"Proceeding of KDD."},{"key":"2023012508051282800_B27","article-title":"COE: a general approach for efficient genome-wide two-locus epistatic test in disease association study","author":"Zhang","year":"2009","journal-title":"Proceeding of RECOMB."},{"key":"2023012508051282800_B28","article-title":"FastChi: an efficient algorithm for analyzing gene-gene interactions","author":"Zhang","year":"2009","journal-title":"Proceeding of PSB."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/12\/i217\/48857979\/bioinformatics_26_12_i217.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/26\/12\/i217\/48857979\/bioinformatics_26_12_i217.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T08:08:45Z","timestamp":1674634125000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/26\/12\/i217\/282883"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,6,1]]},"references-count":28,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2010,6,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btq186","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2010,6,15]]},"published":{"date-parts":[[2010,6,1]]}}}