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  • Brown, Brielin C.New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA (author)

Multiset correlation and factor analysis enables exploration of multi-omics data

  • Article/chapterEnglish2023

Publisher, publication year, extent ...

  • Elsevier BV,2023
  • printrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:kth-337432
  • https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-337432URI
  • https://doi.org/10.1016/j.xgen.2023.100359DOI

Supplementary language notes

  • Language:English
  • Summary in:English

Part of subdatabase

Classification

  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • QC 20231003
  • 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 (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.

Subject headings and genre

Added entries (persons, corporate bodies, meetings, titles ...)

  • Wang, CollinNew York Genome Center, New York, NY, USA; Department of Computer Science, Columbia University, New York, NY, USA (author)
  • Kasela, SilvaNew York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA (author)
  • Aguet, FrançoisIllumina Incorporated, San Francisco, CA, USA; The Broad Institute of MIT and Harvard, Boston, MA, USA (author)
  • Nachun, Daniel C.Department of Pathology, Stanford University, Stanford, CA, USA (author)
  • Taylor, Kent D.Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA (author)
  • Tracy, Russell P.Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA (author)
  • Durda, PeterDepartment of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA (author)
  • Liu, YongmeiDepartment of Medicine, Duke University Medical Center, Durham, NC, USA (author)
  • Johnson, W. CraigDepartment of Biostatistics, University of Washington, Seattle, WA, USA (author)
  • Van Den Berg, DavidDepartment of Clinical Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA (author)
  • Gupta, NamrataThe Broad Institute of MIT and Harvard, Boston, MA, USA (author)
  • Gabriel, StacyThe Broad Institute of MIT and Harvard, Boston, MA, USA (author)
  • Smith, Joshua D.Northwest Genomics Center, University of Washington, Seattle, WA, USA (author)
  • Gerzsten, RobertBeth Israel Deaconess Medical Center, Division of Cardiovascular Medicine, Boston, MA, USA (author)
  • Clish, ClaryThe Broad Institute of MIT and Harvard, Boston, MA, USA (author)
  • Wong, QuennaDepartment of Biostatistics, University of Washington, Seattle, WA, USA (author)
  • Papanicolau, GeorgeDivision of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD, USA (author)
  • Blackwell, Thomas W.Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA (author)
  • Rotter, Jerome I.Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA (author)
  • Rich, Stephen S.Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA (author)
  • Barr, R. GrahamMailman School of Public Health, Columbia University, New York, NY, USA (author)
  • Ardlie, Kristin G.The Broad Institute of MIT and Harvard, Boston, MA, USA (author)
  • Knowles, David A.New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA; Department of Computer Science, Columbia University, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA (author)
  • Lappalainen, TuuliKTH,Genteknologi,Science for Life Laboratory, SciLifeLab,New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA(Swepub:kth)u1o81n30 (author)
  • New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USANew York Genome Center, New York, NY, USA; Department of Computer Science, Columbia University, New York, NY, USA (creator_code:org_t)

Related titles

  • In:Cell Genomics: Elsevier BV3:8, s. 100359-2666-979X

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