{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:41:47Z","timestamp":1786977707074,"version":"build-2736575974"},"reference-count":31,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2013,11,25]],"date-time":"2013-11-25T00:00:00Z","timestamp":1385337600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"NIH","award":["RO1HL105502"],"award-info":[{"award-number":["RO1HL105502"]}]},{"name":"NIH","award":["R01HL116720"],"award-info":[{"award-number":["R01HL116720"]}]},{"name":"NIH","award":["R01CA169122"],"award-info":[{"award-number":["R01CA169122"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genetic Epidemiology"],"published-print":{"date-parts":[[2014,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene\u2010by\u2010gene (G \u00d7 G), or gene\u2010by\u2010environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (\n                    <jats:italic>LRT<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>MV<\/jats:italic>\n                    <\/jats:sub>\n                    ) or either effect alone (\n                    <jats:italic>LRT<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>M<\/jats:italic>\n                    <\/jats:sub>\n                    or\n                    <jats:italic>LRT<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>V<\/jats:italic>\n                    <\/jats:sub>\n                    ) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean\u2010only functional variant, we demonstrate how LD can produce variance\u2010heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D\u2032, and relatively low\n                    <jats:italic>r<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance\u2010only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G \u00d7 G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.\n                  <\/jats:p>","DOI":"10.1002\/gepi.21778","type":"journal-article","created":{"date-parts":[[2013,11,25]],"date-time":"2013-11-25T20:44:14Z","timestamp":1385412254000},"page":"51-59","source":"Crossref","is-referenced-by-count":61,"title":["A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity"],"prefix":"10.1002","volume":"38","author":[{"given":"Ying","family":"Cao","sequence":"first","affiliation":[{"name":"Human Genetics Center School of Public Health The University of Texas Health Science Center Houston Texas United States of America"},{"name":"Division of Biostatistics School of Public Health The University of Texas Health Science Center Houston Texas United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Wei","sequence":"additional","affiliation":[{"name":"Human Genetics Center School of Public Health The University of Texas Health Science Center Houston Texas United States of America"},{"name":"Division of Biostatistics School of Public Health The University of Texas Health Science Center Houston Texas United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Bailey","sequence":"additional","affiliation":[{"name":"Department of Biology Brigham Young University Provo Utah United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John S. K.","family":"Kauwe","sequence":"additional","affiliation":[{"name":"Department of Biology Brigham Young University Provo Utah United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taylor J.","family":"Maxwell","sequence":"additional","affiliation":[{"name":"Human Genetics Center School of Public Health The University of Texas Health Science Center Houston Texas United States of America"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2013,11,25]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2012.00030"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177705688"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.21716"},{"key":"e_1_2_6_5_1","volume-title":"The advance of Bayesian methods for genetic association analysis","author":"Balding DJ","year":"2009"},{"key":"e_1_2_6_6_1","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1111\/j.2517-6161.1954.tb00174.x","article-title":"A note on the multiplying factors for various \u03c72 approximations","volume":"16","author":"Bartlett M.","year":"1954","journal-title":"J R Stat Soc B Stat Methodol"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10519-009-9281-0"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1974.10482955"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-1809.2010.00572.x"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.21671"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.1981.10487680"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511802843"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20607"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20624"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1214\/09-STS301"},{"key":"e_1_2_6_16_1","volume-title":"Nonparametric Statistical Methods","author":"Hollander M","year":"1999"},{"key":"e_1_2_6_17_1","unstructured":"HothornT HornikK vande WielM ZeileisA.2006.Coin: conditional inference procedures in a permutation test framework. 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