Multiset correlation and factor analysis enables exploration of multi-omic data
Multiset correlation and factor analysis enables exploration of multi-omic data
Abstract Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce Multi-set Correlation and Factor Analysis, an unsupervised integration method that enables fast inference of shared and private factors in multi-modal data. Applied to 614 ancestry-diverse participant samples across five ‘omics types, MCFA infers a shared space that captures clinically relevant molecular processes.
Wong Quenna、Gupta Namrata、Gerzsten Robert、Clish Clary、Blackwell Thomas W.、Ardlie Kristin G.、Knowles David A.、Brown Brielin C.、Taylor Kent D.、Tracy Russell P.、Durda Peter、Liu Yongmei、Aguet Fran?ois、Johnson W. Craig、Papanicolau George、Rich Stephen S.、Smith Joshua D.、Rotter Jerome I.、Nachun Daniel C.、Wang Collin、Van Den Berg David、Gabriel Stacy、Kasela Silva、Lappalainen Tuuli
Department of Biostatistics, University of WashingtonThe Broad Institute of MIT and HarvardBeth Israel Deaconess Medical Center, Division of Cardiovascular MedicineThe Broad Institute of MIT and HarvardDepartment of Biostatistics, University of Michigan School of Public HealthThe Broad Institute of MIT and HarvardNew York Genome Center||Data Science Institute, Columbia University||Department of Computer Science, Columbia University||Department of Systems Biology, Columbia UniversityNew York Genome Center||Data Science Institute, Columbia UniversityDepartment of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical CenterDepartment of Pathology and Laboratory Medicine, Larner College of Medicine, University of VermontDepartment of Pathology and Laboratory Medicine, Larner College of Medicine, University of VermontDepartment of Medicine, Duke University Medical CenterIllumina Incorporated||The Broad Institute of MIT and HarvardDepartment of Biostatistics, University of WashingtonDivision of Cardiovascular Sciences, National Heart, Lung, and Blood InstituteCenter for Public Health Genomics, University of VirginiaNorthwest Genomics Center, University of WashingtonDepartment of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical CenterDepartment of Pathology, Stanford UniversityNew York Genome Center||Department of Computer Science, Columbia UniversityDepartment of Clinical Preventative Medicine, Keck School of Medicine, University of Southern CaliforniaThe Broad Institute of MIT and HarvardNew York Genome Center||Department of Systems Biology, Columbia UniversityNew York Genome Center||Department of Systems Biology, Columbia University||Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology
生物科学研究方法、生物科学研究技术生物化学分子生物学
Wong Quenna,Gupta Namrata,Gerzsten Robert,Clish Clary,Blackwell Thomas W.,Ardlie Kristin G.,Knowles David A.,Brown Brielin C.,Taylor Kent D.,Tracy Russell P.,Durda Peter,Liu Yongmei,Aguet Fran?ois,Johnson W. Craig,Papanicolau George,Rich Stephen S.,Smith Joshua D.,Rotter Jerome I.,Nachun Daniel C.,Wang Collin,Van Den Berg David,Gabriel Stacy,Kasela Silva,Lappalainen Tuuli.Multiset correlation and factor analysis enables exploration of multi-omic data[EB/OL].(2025-03-28)[2025-05-09].https://www.biorxiv.org/content/10.1101/2022.07.18.500246.点此复制
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