{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:07:39Z","timestamp":1792786059954,"version":"4.5.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2020,1,24]],"date-time":"2020-01-24T00:00:00Z","timestamp":1579824000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000072","name":"National Institute of Dental and Craniofacial Research","doi-asserted-by":"publisher","award":["R03DE025665"],"award-info":[{"award-number":["R03DE025665"]}],"id":[{"id":"10.13039\/100000072","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Investissement d\u2019Avenir","award":["ANR-16-CONV-0005"],"award-info":[{"award-number":["ANR-16-CONV-0005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Genome-wide association study (GWAS) has been the driving force for identifying association between genetic variants and human phenotypes. Thousands of GWAS summary statistics covering a broad range of human traits and diseases are now publicly available. These GWAS have proven their utility for a range of secondary analyses, including in particular the joint analysis of multiple phenotypes to identify new associated genetic variants. However, although several methods have been proposed, there are very few large-scale applications published so far because of challenges in implementing these methods on real data. Here, we present JASS (Joint Analysis of Summary Statistics), a polyvalent Python package that addresses this need. Our package incorporates recently developed joint tests such as the omnibus approach and various weighted sum of Z-score tests while solving all practical and computational barriers for large-scale multivariate analysis of GWAS summary statistics. This includes data cleaning and harmonization tools, an efficient algorithm for fast derivation of joint statistics, an optimized data management process and a web interface for exploration purposes. Both benchmark analyses and real data applications demonstrated the robustness and strong potential of JASS for the detection of new associated genetic variants. Our package is freely available at https:\/\/gitlab.pasteur.fr\/statistical-genetics\/jass.<\/jats:p>","DOI":"10.1093\/nargab\/lqaa003","type":"journal-article","created":{"date-parts":[[2020,1,24]],"date-time":"2020-01-24T03:37:02Z","timestamp":1579837022000},"source":"Crossref","is-referenced-by-count":28,"title":["JASS: command line and web interface for the joint analysis of GWAS results"],"prefix":"10.1093","volume":"2","author":[{"given":"Hanna","family":"Julienne","sequence":"first","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Lechat","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Guillemot","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carla","family":"Lasry","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunzi","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robinson","family":"Araud","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4946-698X","authenticated-orcid":false,"given":"Vincent","family":"Laville","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bjarni","family":"Vilhjalmsson","sequence":"additional","affiliation":[{"name":"National Center for Register-Based Research, Aarhus University , DK-8210 Aarhus,\u00a0 Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Herv\u00e9","family":"M\u00e9nager","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7554-6783","authenticated-orcid":false,"given":"Hugues","family":"Aschard","sequence":"additional","affiliation":[{"name":"Department of Computational Biology\u2014USR 3756 CNRS,\u00a0Institut Pasteur , 75015 Paris,\u00a0 France"},{"name":"Department of Epidemiology, Harvard T.H. Chan School of Public Health , 02115 Boston, MA,\u00a0 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,1,24]]},"reference":[{"key":"2024030510164866600_B1","doi-asserted-by":"crossref","first-page":"D1005","DOI":"10.1093\/nar\/gky1120","article-title":"The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019","volume":"47","author":"Buniello","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"2024030510164866600_B2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1038\/nrg.2016.142","article-title":"Dissecting the genetics of complex traits using summary association statistics","volume":"18","author":"Pasaniuc","year":"2017","journal-title":"Nat. Rev. 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Genet."},{"key":"2024030510164866600_B8","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":"2024030510164866600_B9","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":"2024030510164866600_B10","doi-asserted-by":"crossref","first-page":"e1007549","DOI":"10.1371\/journal.pgen.1007549","article-title":"Heritability informed power optimization (HIPO) leads to enhanced detection of genetic associations across multiple traits","volume":"14","author":"Qi","year":"2018","journal-title":"PLoS Genet."},{"key":"2024030510164866600_B11","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":"2024030510164866600_B12","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. 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Epidemiol."},{"key":"2024030510164866600_B16","doi-asserted-by":"crossref","first-page":"e1003235","DOI":"10.1371\/journal.pgen.1003235","article-title":"TATES: efficient multivariate genotype\u2013phenotype analysis for genome-wide association studies","volume":"9","author":"van\u00a0der\u00a0Sluis","year":"2013","journal-title":"PLoS Genet."},{"key":"2024030510164866600_B17","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":"2024030510164866600_B18","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/nmeth.2848","article-title":"Efficient multivariate linear mixed model algorithms for genome-wide association studies","volume":"11","author":"Zhou","year":"2014","journal-title":"Nat. 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Epidemiol."},{"key":"2024030510164866600_B34","first-page":"151","article-title":"Grb10 proteins in insulin-like growth factor and insulin receptor signaling (review)","volume":"5","author":"Morrione","year":"2000","journal-title":"Int. J. Mol. Med."},{"key":"2024030510164866600_B35","doi-asserted-by":"crossref","first-page":"2122","DOI":"10.1007\/s00125-009-1463-z","article-title":"A variant in the G6PC2\/ABCB11 locus is associated with increased fasting plasma glucose, increased basal hepatic glucose production and increased insulin release after oral and intravenous glucose loads","volume":"52","author":"Rose","year":"2009","journal-title":"Diabetologia"},{"key":"2024030510164866600_B36","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1038\/ng.764","article-title":"Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47","volume":"43","author":"Anderson","year":"2011","journal-title":"Nat. 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