{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T10:16:00Z","timestamp":1781777760042,"version":"3.54.5"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2016,9,4]],"date-time":"2016-09-04T00:00:00Z","timestamp":1472947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/about_us\/legal\/notices"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM113250, R01HL105397"],"award-info":[{"award-number":["R01GM113250, R01HL105397"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HL116720"],"award-info":[{"award-number":["R01HL116720"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016204","name":"Minnesota Supercomputing Institute","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100016204","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and Implementation<\/jats:title>\n                    <jats:p>The methods are implemented in R package aSPU, freely and publicly available at: https:\/\/cran.r-project.org\/web\/packages\/aSPU\/.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw577","type":"journal-article","created":{"date-parts":[[2016,9,4]],"date-time":"2016-09-04T20:07:40Z","timestamp":1473019660000},"page":"64-71","source":"Crossref","is-referenced-by-count":28,"title":["Gene- and pathway-based association tests for multiple traits with GWAS summary statistics"],"prefix":"10.1093","volume":"33","author":[{"given":"Il-Youp","family":"Kwak","sequence":"first","affiliation":[{"name":"Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Pan","sequence":"additional","affiliation":[{"name":"Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2016,9,4]]},"reference":[{"key":"2023020204305769100_btw577-B1","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1186\/s12711-015-0142-4","article-title":"Genome-wide association study of body weight in Australian Merino sheep reveals an orthologous region on OAR6 to human and bovine genomic regions affecting height and weight","volume":"47","author":"Al-Mamun","year":"2015","journal-title":"Genet. Sel. Evol"},{"key":"2023020204305769100_btw577-B2","first-page":"67","article-title":"A rapid gene-based genome-wide association test with multivariate traits","volume":"71","author":"Basu","year":"2013","journal-title":"Hum. Hered"},{"key":"2023020204305769100_btw577-B3","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/hmg\/ddr489","article-title":"Genome-wide association study of body height in African Americans: the Women\u2019s Health Initiative SNP Health Association Resource (SHARe)","volume":"21","author":"Carty","year":"2012","journal-title":"Hum. Mol. Genet"},{"key":"2023020204305769100_btw577-B4","doi-asserted-by":"crossref","first-page":"1981","DOI":"10.1093\/bioinformatics\/btw052","article-title":"metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis","volume":"32","author":"Cichonska","year":"2016","journal-title":"Bioinformatics"},{"key":"2023020204305769100_btw577-B5","doi-asserted-by":"crossref","first-page":"e1004219.","DOI":"10.1371\/journal.pcbi.1004219","article-title":"Magma: generalized gene-set analysis of gwas data","volume":"11","author":"de Leeuw","year":"2015","journal-title":"PLoS Comput. Biol"},{"key":"2023020204305769100_btw577-B6","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1534\/genetics.115.178343","article-title":"Gene level meta-analysis of quantitative traits by functional linear models","volume":"200","author":"Fan","year":"2015","journal-title":"Genetics"},{"key":"2023020204305769100_btw577-B7","doi-asserted-by":"crossref","DOI":"10.1534\/genetics.115.180869","article-title":"Meta-analysis of complex diseases at gene level by generalized functional linear models","author":"Fan","year":"2016","journal-title":"Genetics, To Appear"},{"key":"2023020204305769100_btw577-B8","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1186\/1756-0500-4-386","article-title":"Comparisons of seven algorithms for pathway analysis using the wtccc crohns disease dataset","volume":"4","author":"Gui","year":"2011","journal-title":"BMC Res. Notes"},{"key":"2023020204305769100_btw577-B9","volume-title":"Matrix Variate Distributions","author":"Gupta","year":"1999"},{"key":"2023020204305769100_btw577-B10","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1038\/ng.2477","article-title":"New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism","volume":"45","author":"Horikoshi","year":"2013","journal-title":"Nat. Genet"},{"key":"2023020204305769100_btw577-B12","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1002\/gepi.21931","article-title":"An adaptive association test for multiple phenotypes with GWAS summary statistics","volume":"39","author":"Kim","year":"2015","journal-title":"Genet. Epidemiol"},{"key":"2023020204305769100_btw577-B13","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1534\/genetics.115.186502","article-title":"Powerful and adaptive testing for multi-trait and multi-SNP associations with GWAS and sequencing data","volume":"203","author":"Kim","year":"2016","journal-title":"Genetics"},{"key":"2023020204305769100_btw577-B14","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1093\/bioinformatics\/btv719","article-title":"Adaptive gene-and pathway-trait association testing with GWAS summary statistics","volume":"32","author":"Kwak","year":"2016","journal-title":"Bioinformatics"},{"key":"2023020204305769100_btw577-B15","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":"2023020204305769100_btw577-B16","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1016\/j.ajhg.2012.08.004","article-title":"Hyst: a hybrid set-based test for genome-wide association studies, with application to protein-protein interaction-based association analysis","volume":"91","author":"Li","year":"2012","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B17","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1016\/j.ajhg.2011.07.015","article-title":"A general framework for detecting disease associations with rare variants in sequencing studies","volume":"89","author":"Lin","year":"2011","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B201","first-page":"478","article-title":"A versatile gene-based test for genome-wide association studies","volume":"91","author":"Liu","year":"2010","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B18","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1002\/gepi.21663","article-title":"Multivariate phenotype association analysis by marker-set kernel machine regression","volume":"36","author":"Maity","year":"2012","journal-title":"Genet. Epidemiol"},{"key":"2023020204305769100_btw577-B19","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1038\/nature08494","article-title":"Finding the missing heritability of complex diseases","volume":"461","author":"Manolio","year":"2009","journal-title":"Nature"},{"key":"2023020204305769100_btw577-B20","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1890\/0012-9658(2001)082[0290:FMMTCD]2.0.CO;2","article-title":"Fitting multivariate models to community data: a comment on distance-based redundancy analysis","volume":"82","author":"McArdle","year":"2001","journal-title":"Ecology"},{"key":"2023020204305769100_btw577-B21","doi-asserted-by":"crossref","first-page":"e56497","DOI":"10.1371\/journal.pone.0056497","article-title":"Expression levels of LCORL are associated with body size in horses","volume":"8","author":"Metzger","year":"2013","journal-title":"PLoS One"},{"key":"2023020204305769100_btw577-B23","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1534\/genetics.114.165035","article-title":"A powerful and adaptive association test for rare variants","volume":"197","author":"Pan","year":"2014","journal-title":"Genetics"},{"key":"2023020204305769100_btw577-B24","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.ajhg.2015.05.018","article-title":"A powerful pathway-based adaptive test for genetic association with common or rare variants","volume":"97","author":"Pan","year":"2015","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B25","doi-asserted-by":"crossref","first-page":"e1003500","DOI":"10.1371\/journal.pgen.1003500","article-title":"Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits","volume":"9","author":"Randall","year":"2013","journal-title":"PLoS Genet"},{"key":"2023020204305769100_btw577-B26","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1086\/429838","article-title":"Nonparametric tests of association of multiple genes with human disease","volume":"76","author":"Schaid","year":"2005","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B27","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1016\/j.neuroimage.2010.01.042","article-title":"Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: a study of the ADNI cohort","volume":"53","author":"Shen","year":"2010","journal-title":"NeuroImage"},{"key":"2023020204305769100_btw577-B28","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1093\/bioinformatics\/btu783","article-title":"MGAS: a powerful tool for multivariate gene-based genome-wide association analysis","volume":"31","author":"Van der Sluis","year":"2015","journal-title":"Bioinformatics"},{"key":"2023020204305769100_btw577-B29","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":"2023020204305769100_btw577-B30","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1002\/gepi.21895","article-title":"Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models","volume":"39","author":"Wang","year":"2015","journal-title":"Genet. Epidemiol"},{"key":"2023020204305769100_btw577-B31","doi-asserted-by":"crossref","first-page":"e0150975.","DOI":"10.1371\/journal.pone.0150975","article-title":"Joint analysis of multiple traits using \u201cOptimal\u201d maximum heritability test","volume":"11","author":"Wang","year":"2016","journal-title":"PLoS One"},{"key":"2023020204305769100_btw577-B32","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1086\/508346","article-title":"Generalized genomic distance-based regression methodology for multilocus association analysis","volume":"79","author":"Wessel","year":"2006","journal-title":"Am. J. Hum. Genet"},{"key":"2023020204305769100_btw577-B33","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":"Wellcome Trust Case Control Consortium","year":"2007","journal-title":"Nature"},{"key":"2023020204305769100_btw577-B34","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":"2023020204305769100_btw577-B35","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1002\/gepi.20497","article-title":"Analyze multivariate phenotypes in genetic association studies by combining univariate association tests","volume":"34","author":"Yang","year":"2010","journal-title":"Genet. Epidemiol"},{"key":"2023020204305769100_btw577-B36","article-title":"Methods for analyzing multivariate phenotypes in genetic association studies","volume":"2012","author":"Yang","year":"2013","journal-title":"J. Prob. Stat"},{"key":"2023020204305769100_btw577-B37","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.neuroimage.2014.03.061","article-title":"Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data","volume":"96","author":"Zhang","year":"2014","journal-title":"NeuroImage"},{"key":"2023020204305769100_btw577-B38","doi-asserted-by":"crossref","first-page":"532","DOI":"10.1214\/13-AOS1187","article-title":"Gemini: graph estimation with matrix variate normal instances","volume":"42","author":"Zhou","year":"2014","journal-title":"Ann. Stat"},{"key":"2023020204305769100_btw577-B39","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.ajhg.2014.11.011","article-title":"Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension","volume":"96","author":"Zhu","year":"2015","journal-title":"Am. J. Hum. Genet"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/1\/64\/49037324\/bioinformatics_33_1_64.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/33\/1\/64\/49037324\/bioinformatics_33_1_64.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T23:32:16Z","timestamp":1675294336000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/33\/1\/64\/2525686"}},"subtitle":[],"editor":[{"given":"Oliver","family":"Stegle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2016,9,4]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw577","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/052068","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2017,1,1]]},"published":{"date-parts":[[2016,9,4]]}}}