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This AutoML approach discovers variants with higher predictive performance compared to standard GWAS methods, computes an individual risk prediction score, generalizes to new, unseen data, is shown to better differentiate causal variants from other highly correlated variants, and enhances knowledge discovery and interpretability by reporting multiple equivalent biosignatures.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>Code for this study is available at: https:\/\/github.com\/mensxmachina\/autoML-GWAS. JADBio offers a free version at: https:\/\/jadbio.com\/sign-up\/. SNP data can be downloaded from the EGA repository (https:\/\/ega-archive.org\/). PRS data are found at: https:\/\/www.aicrowd.com\/challenges\/opensnp-height-prediction. Simulation data to study population structure can be found at: https:\/\/easygwas.ethz.ch\/data\/public\/dataset\/view\/1\/.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad545","type":"journal-article","created":{"date-parts":[[2023,9,5]],"date-time":"2023-09-05T13:30:53Z","timestamp":1693920653000},"source":"Crossref","is-referenced-by-count":17,"title":["Automated machine learning for genome wide association studies"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0442-2211","authenticated-orcid":false,"given":"Kleanthi","family":"Lakiotaki","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Crete , Heraklion, Greece"}]},{"given":"Zaharias","family":"Papadovasilakis","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Crete , Heraklion, Greece"},{"name":"JADBio Gnosis DA S.A., Science and Technology Park of Crete , GR-70013 Heraklion, 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