{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:34:22Z","timestamp":1772138062787,"version":"3.50.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T00:00:00Z","timestamp":1704672000000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"St. Baldrick\u2019s Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Multi-trait analysis has been shown to have greater statistical power than single-trait analysis. Most of the existing multi-trait analysis methods only work with a limited number of traits and usually prioritize high statistical power over identifying relevant traits, which heavily rely on domain knowledge.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>To handle diseases and traits with obscure etiology, we developed TraitScan, a powerful and fast algorithm that identifies potential pleiotropic traits from a moderate or large number of traits (e.g. dozens to thousands) and tests the association between one genetic variant and the selected traits. TraitScan can handle either individual-level or summary-level GWAS data. We evaluated TraitScan using extensive simulations and found that it outperformed existing methods in terms of both testing power and trait selection when sparsity was low or modest. We then applied it to search for traits associated with Ewing Sarcoma, a rare bone tumor with peak onset in adolescence, among 754 traits in UK Biobank. Our analysis revealed a few promising traits worthy of further investigation, highlighting the use of TraitScan for more effective multi-trait analysis as biobanks emerge. We also extended TraitScan to search and test association with a polygenic risk score and genetically imputed gene expression.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Our algorithm is implemented in an R package \u201cTraitScan\u201d available at https:\/\/github.com\/RuiCao34\/TraitScan.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad777","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T23:26:47Z","timestamp":1704756407000},"source":"Crossref","is-referenced-by-count":0,"title":["Subset scanning for multi-trait analysis using GWAS summary statistics"],"prefix":"10.1093","volume":"40","author":[{"given":"Rui","family":"Cao","sequence":"first","affiliation":[{"name":"Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota , Minneapolis, MN 55414, United States"}]},{"given":"Evan","family":"Olawsky","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota , Minneapolis, MN 55414, United States"}]},{"suffix":"III","given":"Edward","family":"McFowland","sequence":"additional","affiliation":[{"name":"Technology and Operations Management, Harvard Business School, Harvard University , Boston, MA 02163, United States"}]},{"given":"Erin","family":"Marcotte","sequence":"additional","affiliation":[{"name":"Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota , Minneapolis, MN 55454, United States"}]},{"given":"Logan","family":"Spector","sequence":"additional","affiliation":[{"name":"Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota , Minneapolis, MN 55454, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0162-7740","authenticated-orcid":false,"given":"Tianzhong","family":"Yang","sequence":"additional","affiliation":[{"name":"Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota , Minneapolis, MN 55414, United States"},{"name":"Division of Epidemiology and Clinical Research, Department of Pediatrics, University of Minnesota , Minneapolis, MN 55454, United States"}]}],"member":"286","published-online":{"date-parts":[[2024,1,5]]},"reference":[{"key":"2024051105035592600_btad777-B1","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nature15393","article-title":"A global reference for human genetic variation","volume":"526","author":"Auton","year":"2015","journal-title":"Nature"},{"key":"2024051105035592600_btad777-B2","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1080\/01621459.2016.1192039","article-title":"The generalized higher criticism for testing SNP-set effects in genetic association studies","volume":"112","author":"Barnett","year":"2017","journal-title":"J Am Stat Assoc"},{"key":"2024051105035592600_btad777-B3","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1016\/j.ajhg.2012.03.015","article-title":"A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits","volume":"90","author":"Bhattacharjee","year":"2012","journal-title":"Am J Hum Genet"},{"key":"2024051105035592600_btad777-B4","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1002\/gepi.22330","article-title":"Truncated tests for combining evidence of summary statistics","volume":"44","author":"Bu","year":"2020","journal-title":"Genet Epidemiol"},{"key":"2024051105035592600_btad777-B5","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","article-title":"The UK Biobank resource with deep phenotyping and genomic data","volume":"562","author":"Bycroft","year":"2018","journal-title":"Nature"},{"key":"2024051105035592600_btad777-B6","doi-asserted-by":"crossref","first-page":"7117","DOI":"10.1038\/s41467-021-27438-7","article-title":"Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors","volume":"12","author":"Chen","year":"2021","journal-title":"Nat Commun"},{"key":"2024051105035592600_btad777-B7","doi-asserted-by":"crossref","first-page":"7274","DOI":"10.1038\/s41467-021-26970-w","article-title":"Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics","volume":"12","author":"Darrous","year":"2021","journal-title":"Nat Commun"},{"key":"2024051105035592600_btad777-B8","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1093\/bioinformatics\/btq126","article-title":"PHEWAS: demonstrating the feasibility of a phenome-wide scan to discover gene\u2013disease associations","volume":"26","author":"Denny","year":"2010","journal-title":"Bioinformatics"},{"key":"2024051105035592600_btad777-B9","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1038\/s41467-018-06540-3","article-title":"Phenome-wide association studies across large population cohorts support drug target validation","volume":"9","author":"Diogo","year":"2018","journal-title":"Nat Commun"},{"key":"2024051105035592600_btad777-B10","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1002\/gepi.22391","article-title":"Multitrait transcriptome-wide association study (TWAS) tests","volume":"45","author":"Feng","year":"2021","journal-title":"Genet Epidemiol"},{"key":"2024051105035592600_btad777-B11","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1038\/ng.3404","article-title":"Partitioning heritability by functional annotation using genome-wide association summary statistics","volume":"47","author":"Finucane","year":"2015","journal-title":"Nat Genet"},{"key":"2024051105035592600_btad777-B12","first-page":"17","article-title":"IGF1R immunohistochemistry in Ewing\u2019s sarcoma as predictor of response to targeted therapy","volume":"14","author":"Gonzalez","year":"2020","journal-title":"Int J Health Sci"},{"key":"2024051105035592600_btad777-B13","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1038\/gim.2013.72","article-title":"The electronic medical records and genomics (emerge) network: past, present, and future","volume":"15","author":"Gottesman","year":"2013","journal-title":"Genet Med"},{"key":"2024051105035592600_btad777-B14","doi-asserted-by":"crossref","first-page":"e1007081","DOI":"10.1371\/journal.pgen.1007081","article-title":"Orienting the causal relationship between imprecisely measured traits using GWAS summary data","volume":"13","author":"Hemani","year":"2017","journal-title":"PLoS Genet"},{"key":"2024051105035592600_btad777-B15","doi-asserted-by":"crossref","first-page":"e34408","DOI":"10.7554\/eLife.34408","article-title":"The MR-Base platform supports systematic causal inference across the human phenome","volume":"7","author":"Hemani","year":"2018","journal-title":"Elife"},{"key":"2024051105035592600_btad777-B16","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1002\/gepi.22259","article-title":"Summary statistic analyses can mistake confounding bias for heritability","volume":"43","author":"Holmes","year":"2019","journal-title":"Genet Epidemiol"},{"key":"2024051105035592600_btad777-B17","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/00031305.2016.1277159","article-title":"Optimal whitening and decorrelation","volume":"72","author":"Kessy","year":"2018","journal-title":"Am Stat"},{"key":"2024051105035592600_btad777-B18","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":"2024051105035592600_btad777-B19","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.suc.2008.03.006","article-title":"Sarcoma epidemiology and etiology: potential environmental and genetic factors","volume":"88","author":"Lahat","year":"2008","journal-title":"Surg Clin N Am"},{"key":"2024051105035592600_btad777-B20","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ajhg.2023.01.017","article-title":"Targeted long-read sequencing of the Ewing sarcoma 6p25. 1 susceptibility locus identifies germline-somatic interactions with EWSR1-FLI1 binding","volume":"110","author":"Lee","year":"2023","journal-title":"Am J Hum Genet"},{"key":"2024051105035592600_btad777-B21","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1186\/s13073-020-00742-5","article-title":"Polygenic risk scores: from research tools to clinical instruments","volume":"12","author":"Lewis","year":"2020","journal-title":"Genome Med"},{"key":"2024051105035592600_btad777-B22","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.3390\/biomedicines10061325","article-title":"Epigenetic and transcriptional signaling in Ewing sarcoma\u2014disease etiology and therapeutic opportunities","volume":"10","author":"Li","year":"2022","journal-title":"Biomedicines"},{"key":"2024051105035592600_btad777-B23","doi-asserted-by":"crossref","first-page":"665252","DOI":"10.3389\/fgene.2021.665252","article-title":"Improved estimation of phenotypic correlations using summary association statistics","volume":"12","author":"Li","year":"2021","journal-title":"Front Genet"},{"key":"2024051105035592600_btad777-B24","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1007\/978-1-4939-7274-6_22","volume-title":"Statistical Human Genetics","author":"Li","year":"2017"},{"key":"2024051105035592600_btad777-B25","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1111\/biom.12735","article-title":"Multiple phenotype association tests using summary statistics in genome-wide association studies","volume":"74","author":"Liu","year":"2018","journal-title":"Biometrics"},{"key":"2024051105035592600_btad777-B26","doi-asserted-by":"crossref","first-page":"3184","DOI":"10.1038\/s41467-018-05537-2","article-title":"Genome-wide association study identifies multiple new loci associated with Ewing sarcoma susceptibility","volume":"9","author":"Machiela","year":"2018","journal-title":"Nat Commun"},{"key":"2024051105035592600_btad777-B27","first-page":"1533","article-title":"Fast generalized subset scan for anomalous pattern detection","volume":"14","author":"McFowland","year":"2013","journal-title":"J Mach Learn Res"},{"key":"2024051105035592600_btad777-B28","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1111\/j.1467-9868.2011.01014.x","article-title":"Fast subset scan for spatial pattern detection: fast subset scan","volume":"74","author":"Neill","year":"2012","journal-title":"J R Stat Soc Ser B (Stat Methodol)"},{"key":"2024051105035592600_btad777-B29","doi-asserted-by":"crossref","first-page":"e34861","DOI":"10.1371\/journal.pone.0034861","article-title":"Multiphen: joint model of multiple phenotypes can increase discovery in GWAS","volume":"7","author":"O\u2019Reilly","year":"2012","journal-title":"PloS One"},{"key":"2024051105035592600_btad777-B30","doi-asserted-by":"crossref","first-page":"e1008271","DOI":"10.1371\/journal.pcbi.1008271","article-title":"Penalized regression and model selection methods for polygenic scores on summary statistics","volume":"16","author":"Pattee","year":"2020","journal-title":"PLoS Comput Biol"},{"key":"2024051105035592600_btad777-B31","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1038\/ng.1085","article-title":"Common variants near TARDBP and EGR2 are associated with susceptibility to ewing sarcoma","volume":"44","author":"Postel-Vinay","year":"2012","journal-title":"Nat Genet"},{"key":"2024051105035592600_btad777-B32","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1111\/cts.12522","article-title":"Genome-wide and phenome-wide approaches to understand variable drug actions in electronic health records","volume":"11","author":"Robinson","year":"2018","journal-title":"Clin Transl Sci"},{"key":"2024051105035592600_btad777-B33","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1038\/clpt.2008.89","article-title":"Development of a large-scale de-identified DNA biobank to enable personalized medicine","volume":"84","author":"Roden","year":"2008","journal-title":"Clin Pharmacol Ther"},{"key":"2024051105035592600_btad777-B34","doi-asserted-by":"crossref","first-page":"31","DOI":"10.4103\/0973-029X.37800","article-title":"Ewing\u2019s sarcoma of the mandible","volume":"10","author":"Sharada","year":"2006","journal-title":"J Oral Maxillofac Pathol"},{"key":"2024051105035592600_btad777-B35","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1002\/ijc.33674","article-title":"Comparative international incidence of Ewing sarcoma 1988 to 2012","volume":"149","author":"Spector","year":"2021","journal-title":"Int J Cancer"},{"key":"2024051105035592600_btad777-B36","doi-asserted-by":"crossref","first-page":"e1001779","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"Sudlow","year":"2015","journal-title":"PLoS Med"},{"key":"2024051105035592600_btad777-B37","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1038\/s41576-018-0018-x","article-title":"The personal and clinical utility of polygenic risk scores","volume":"19","author":"Torkamani","year":"2018","journal-title":"Nat Rev Genet"},{"key":"2024051105035592600_btad777-B38","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1038\/s41586-023-05844-9","article-title":"An atlas of genetic scores to predict multi-omic traits","volume":"616","author":"Xu","year":"2023","journal-title":"Nature"},{"key":"2024051105035592600_btad777-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\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btad777\/55152235\/btad777.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/1\/btad777\/57512178\/btad777.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/1\/btad777\/57512178\/btad777.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T01:14:39Z","timestamp":1715390079000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btad777\/7513162"}},"subtitle":[],"editor":[{"given":"Russell","family":"Schwartz","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2024,1,1]]},"references-count":39,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btad777","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.07.19.23292708","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":[[2024,1,1]]},"published":{"date-parts":[[2024,1,1]]},"article-number":"btad777"}}