{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T03:22:08Z","timestamp":1776396128982,"version":"3.51.2"},"reference-count":41,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2019,1,18]],"date-time":"2019-01-18T00:00:00Z","timestamp":1547769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["U19AI118608"],"award-info":[{"award-number":["U19AI118608"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"NHMRC","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Career Development","award":["GNT1087415"],"award-info":[{"award-number":["GNT1087415"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>In the continuously expanding omics era, novel computational and statistical strategies are needed for data integration and identification of biomarkers and molecular signatures. We present Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO), a multi-omics integrative method that seeks for common information across different data types through the selection of a subset of molecular features, while discriminating between multiple phenotypic groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Using simulations and benchmark multi-omics studies, we show that DIABLO identifies features with superior biological relevance compared with existing unsupervised integrative methods, while achieving predictive performance comparable to state-of-the-art supervised approaches. DIABLO is versatile, allowing for modular-based analyses and cross-over study designs. In two case studies, DIABLO identified both known and novel multi-omics biomarkers consisting of mRNAs, miRNAs, CpGs, proteins and metabolites.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>DIABLO is implemented in the mixOmics R Bioconductor package with functions for parameters\u2019 choice and visualization to assist in the interpretation of the integrative analyses, along with tutorials on http:\/\/mixomics.org and in our Bioconductor vignette.<\/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\/bty1054","type":"journal-article","created":{"date-parts":[[2019,1,14]],"date-time":"2019-01-14T07:08:24Z","timestamp":1547449704000},"page":"3055-3062","source":"Crossref","is-referenced-by-count":893,"title":["DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays"],"prefix":"10.1093","volume":"35","author":[{"given":"Amrit","family":"Singh","sequence":"first","affiliation":[{"name":"University of British Columbia Prevention of Organ Failure (PROOF) Centre of Excellence, , Vancouver, BC, Canada"}]},{"given":"Casey P","family":"Shannon","sequence":"additional","affiliation":[{"name":"University of British Columbia Prevention of Organ Failure (PROOF) Centre of Excellence, , Vancouver, BC, Canada"}]},{"given":"Beno\u00eet","family":"Gautier","sequence":"additional","affiliation":[{"name":"University of Queensland Diamantina Institute, Translational Research Institute The , Woolloongabba, Queensland, Australia"}]},{"given":"Florian","family":"Rohart","sequence":"additional","affiliation":[{"name":"Institute for Molecular Bioscience, The University of Queensland , St Lucia, Queensland, Australia"}]},{"given":"Micha\u00ebl","family":"Vacher","sequence":"additional","affiliation":[{"name":"Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation , Brisbane, Queensland, Australia"}]},{"given":"Scott J","family":"Tebbutt","sequence":"additional","affiliation":[{"name":"University of British Columbia Prevention of Organ Failure (PROOF) Centre of Excellence, , Vancouver, BC, Canada"}]},{"given":"Kim-Anh","family":"L\u00ea Cao","sequence":"additional","affiliation":[{"name":"Melbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne , Melbourne, Australia"}]}],"member":"286","published-online":{"date-parts":[[2019,1,18]]},"reference":[{"key":"2023062711304933500_bty1054-B1","doi-asserted-by":"crossref","first-page":"i413","DOI":"10.1093\/bioinformatics\/btw449","article-title":"Tandem: a two-stage approach to maximize interpretability of drug response models based on multiple molecular data types","volume":"32","author":"Aben","year":"2016","journal-title":"Bioinformatics"},{"key":"2023062711304933500_bty1054-B2","doi-asserted-by":"crossref","first-page":"i311","DOI":"10.1093\/bioinformatics\/btv255","article-title":"Feral: network-based classifier with application to breast cancer outcome prediction","volume":"31","author":"Allahyar","year":"2015","journal-title":"Bioinformatics"},{"key":"2023062711304933500_bty1054-B3","doi-asserted-by":"crossref","first-page":"e8124","DOI":"10.15252\/msb.20178124","article-title":"Multi-omics factor analysis\u2014a framework for unsupervised integration of multi-omics data sets","volume":"14","author":"Argelaguet","year":"2018","journal-title":"Mol. 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