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Sökning: WFRF:(Barr Graham) > Multiset correlatio...

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

Brown, Brielin C. (författare)
New York Genome Center, New York, NY, USA; Data Science Institute, Columbia University, New York, NY, USA
Wang, Collin (författare)
New York Genome Center, New York, NY, USA; Department of Computer Science, Columbia University, New York, NY, USA
Kasela, Silva (författare)
New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA
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Aguet, François (författare)
Illumina Incorporated, San Francisco, CA, USA; The Broad Institute of MIT and Harvard, Boston, MA, USA
Nachun, Daniel C. (författare)
Department of Pathology, Stanford University, Stanford, CA, USA
Taylor, Kent D. (författare)
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
Tracy, Russell P. (författare)
Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
Durda, Peter (författare)
Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
Liu, Yongmei (författare)
Department of Medicine, Duke University Medical Center, Durham, NC, USA
Johnson, W. Craig (författare)
Department of Biostatistics, University of Washington, Seattle, WA, USA
Van Den Berg, David (författare)
Department of Clinical Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
Gupta, Namrata (författare)
The Broad Institute of MIT and Harvard, Boston, MA, USA
Gabriel, Stacy (författare)
The Broad Institute of MIT and Harvard, Boston, MA, USA
Smith, Joshua D. (författare)
Northwest Genomics Center, University of Washington, Seattle, WA, USA
Gerzsten, Robert (författare)
Beth Israel Deaconess Medical Center, Division of Cardiovascular Medicine, Boston, MA, USA
Clish, Clary (författare)
The Broad Institute of MIT and Harvard, Boston, MA, USA
Wong, Quenna (författare)
Department of Biostatistics, University of Washington, Seattle, WA, USA
Papanicolau, George (författare)
Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
Blackwell, Thomas W. (författare)
Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
Rotter, Jerome I. (författare)
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
Rich, Stephen S. (författare)
Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
Barr, R. Graham (författare)
Mailman School of Public Health, Columbia University, New York, NY, USA
Ardlie, Kristin G. (författare)
The Broad Institute of MIT and Harvard, Boston, MA, USA
Knowles, David A. (författare)
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
Lappalainen, Tuuli (författare)
KTH,Genteknologi,Science for Life Laboratory, SciLifeLab,New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA
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 (creator_code:org_t)
Elsevier BV, 2023
2023
Engelska.
Ingår i: Cell Genomics. - : Elsevier BV. - 2666-979X. ; 3:8, s. 100359-
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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.

Ämnesord

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
NATURVETENSKAP  -- Biologi -- Genetik (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Genetics (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Medicinsk genetik (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Medical Genetics (hsv//eng)

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