{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T22:00:00Z","timestamp":1758405600053,"version":"3.37.3"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2018,10,11]],"date-time":"2018-10-11T00:00:00Z","timestamp":1539216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"National Science Funding of China","award":["22302815","12316116","12301417","16307818","61501389","11501440"],"award-info":[{"award-number":["22302815","12316116","12301417","16307818","61501389","11501440"]}]},{"name":"Hong Kong Research Grant Council","award":["IGN17SC02"],"award-info":[{"award-number":["IGN17SC02"]}]},{"DOI":"10.13039\/501100001839","name":"University Grants Committee","doi-asserted-by":"publisher","award":["R9405"],"award-info":[{"award-number":["R9405"]}],"id":[{"id":"10.13039\/501100001839","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005950","name":"The Hong Kong University of Science and Technology","doi-asserted-by":"crossref","award":["Duke-NUS Medical School WBS: R-913-200-098-263","MOE2016-T2-2-029"],"award-info":[{"award-number":["Duke-NUS Medical School WBS: R-913-200-098-263","MOE2016-T2-2-029"]}],"id":[{"id":"10.13039\/501100005950","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001459","name":"Ministry of Eduction, Singapore","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001459","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012271","name":"Shenzhen Fundamental Research Fund","doi-asserted-by":"crossref","award":["KQTD2015033114415450"],"award-info":[{"award-number":["KQTD2015033114415450"]}],"id":[{"id":"10.13039\/501100012271","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,5,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>A large number of recent genome-wide association studies (GWASs) for complex phenotypes confirm the early conjecture for polygenicity, suggesting the presence of large number of variants with only tiny or moderate effects. However, due to the limited sample size of a single GWAS, many associated genetic variants are too weak to achieve the genome-wide significance. These undiscovered variants further limit the prediction capability of GWAS. Restricted access to the individual-level data and the increasing availability of the published GWAS results motivate the development of methods integrating both the individual-level and summary-level data. How to build the connection between the individual-level and summary-level data determines the efficiency of using the existing abundant summary-level resources with limited individual-level data, and this issue inspires more efforts in the existing area.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this study, we propose a novel statistical approach, LEP, which provides a novel way of modeling the connection between the individual-level data and summary-level data. LEP integrates both types of data by LEveraging Pleiotropy to increase the statistical power of risk variants identification and the accuracy of risk prediction. The algorithm for parameter estimation is developed to handle genome-wide-scale data. Through comprehensive simulation studies, we demonstrated the advantages of LEP over the existing methods. We further applied LEP to perform integrative analysis of Crohn\u2019s disease from WTCCC and summary statistics from GWAS of some other diseases, such as Type 1 diabetes, Ulcerative colitis and Primary biliary cirrhosis. LEP was able to significantly increase the statistical power of identifying risk variants and improve the risk prediction accuracy from 63.39% (\u00b10.58%) to 68.33% (\u00b10.32%) using about 195 000 variants.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The LEP software is available at https:\/\/github.com\/daviddaigithub\/LEP.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty870","type":"journal-article","created":{"date-parts":[[2018,10,10]],"date-time":"2018-10-10T07:06:46Z","timestamp":1539155206000},"page":"1729-1736","source":"Crossref","is-referenced-by-count":5,"title":["Joint analysis of individual-level and summary-level GWAS data by leveraging pleiotropy"],"prefix":"10.1093","volume":"35","author":[{"given":"Mingwei","family":"Dai","sequence":"first","affiliation":[{"name":"Department of Applied Mathematics, School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China"},{"name":"Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Wan","sequence":"additional","affiliation":[{"name":"ShenZhen Research Institute of Big Data, ShenZhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Liu","sequence":"additional","affiliation":[{"name":"Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"Centre for Quantitative Medicine, Program in Health Services and Systems Research, Duke-NUS Medical School, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongben","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Can","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,10,11]]},"reference":[{"key":"2023013107485915600_bty870-B1","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1086\/422827","article-title":"A missense single-nucleotide polymorphism in a gene encoding a protein tyrosine phosphatase (PTPN22) is associated with rheumatoid arthritis","volume":"75","author":"Begovich","year":"2004","journal-title":"Am. 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