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The neurodegenerative disorders usually exhibit the diversity and heterogeneity, originating from which different diagnostic groups might carry distinct imaging QTs, SNPs and their interactions. Sparse canonical correlation analysis (SCCA) is widely used to identify bi-multivariate genotype\u2013phenotype associations. However, most existing SCCA methods are unsupervised, leading to an inability to identify diagnosis-specific genotype\u2013phenotype associations.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this article, we propose a new joint multitask learning method, named MT\u2013SCCALR, which absorbs the merits of both SCCA and logistic regression. MT\u2013SCCALR learns genotype\u2013phenotype associations of multiple tasks jointly, with each task focusing on identifying one diagnosis-specific genotype\u2013phenotype pattern. Meanwhile, MT\u2013SCCALR cannot only select relevant SNPs and imaging QTs for each diagnostic group alone, but also allows the selection of those shared by multiple diagnostic groups. We derive an efficient optimization algorithm whose convergence to a local optimum is guaranteed. Compared with two state-of-the-art methods, MT\u2013SCCALR yields better or similar canonical correlation coefficients and classification performances. In addition, it owns much better discriminative canonical weight patterns of great interest than competitors. This demonstrates the power and capability of MTSCCAR in identifying diagnostically heterogeneous genotype\u2013phenotype patterns, which would be helpful to understand the pathophysiology of brain disorders.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The software is publicly available at https:\/\/github.com\/dulei323\/MTSCCALR.<\/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\/btaa434","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T12:13:01Z","timestamp":1588594381000},"page":"i371-i379","source":"Crossref","is-referenced-by-count":35,"title":["Identifying diagnosis-specific genotype\u2013phenotype associations via joint multitask sparse canonical correlation analysis and classification"],"prefix":"10.1093","volume":"36","author":[{"given":"Lei","family":"Du","sequence":"first","affiliation":[{"name":"Department of intelligent science and technology, School of Automation, Northwestern Polytechnical University , Xi\u2019an 710072, China"}]},{"given":"Fang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of intelligent science and technology, School of Automation, Northwestern Polytechnical University , Xi\u2019an 710072, China"}]},{"given":"Kefei","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104, USA"}]},{"given":"Xiaohui","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104, USA"}]},{"given":"Shannon L","family":"Risacher","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences, Indiana University School of Medicine , Indianapolis, IN 46202, USA"}]},{"given":"Junwei","family":"Han","sequence":"additional","affiliation":[{"name":"Department of intelligent science and technology, School of Automation, Northwestern Polytechnical University , Xi\u2019an 710072, China"}]},{"given":"Lei","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of intelligent science and technology, School of Automation, Northwestern Polytechnical University , Xi\u2019an 710072, China"}]},{"given":"Andrew J","family":"Saykin","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences, Indiana University School of Medicine , Indianapolis, IN 46202, USA"}]},{"given":"Li","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104, USA"}]},{"name":"for the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[]}],"member":"286","published-online":{"date-parts":[[2020,7,13]]},"reference":[{"key":"2024021913330942400_btaa434-B1","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.jalz.2013.02.003","article-title":"2013 Alzheimer\u2019s disease facts and figures","volume":"9","year":"2013","journal-title":"Alzheimers Dement"},{"key":"2024021913330942400_btaa434-B2","first-page":"368","article-title":"Back to the future: Alzheimer\u2019s disease heterogeneity revisited. 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