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Response to Ramos et al

  • Eleanor G. Seaby
    Correspondence
    Correspondence and requests for materials should be addressed to Eleanor G. Seaby, University Hospital Southampton, MP 808, Duthie Building, Tremona Road, Southampton, SO16 6YD, United Kingdom.
    Affiliations
    Faculty of Medicine, University of Southampton, Southampton, United Kingdom

    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA

    Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA

    Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA
    Search for articles by this author
  • Diana Baralle
    Affiliations
    Faculty of Medicine, University of Southampton, Southampton, United Kingdom
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  • Heidi L. Rehm
    Affiliations
    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA

    Center for Genomic Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA
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  • Anne O’Donnell-Luria
    Affiliations
    Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA

    Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA
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  • Sarah Ennis
    Affiliations
    Faculty of Medicine, University of Southampton, Southampton, United Kingdom
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Published:September 19, 2022DOI:https://doi.org/10.1016/j.gim.2022.08.016
      We thank Ramos et al
      • Kitajima J.P.
      • de Athayde Costa L.S.
      • Monteiro F.P.
      • Kok F.
      Ramos LLP
      Correspondence on “A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes” by Seaby et al.
      for their correspondence and interest in our recent article that applied constraint metrics to uplift novel disease gene discovery.
      • Seaby E.G.
      • Smedley D.
      • Taylor Tavares A.L.
      • et al.
      A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes.
      The authors provide valuable insight by applying an approach similar to ours to identify novel genes using single sample (as opposed to trio) exome sequencing in Brazil and in narrowing the gap of health inequality in genetic testing.
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