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Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data.
Singer-Berk, Moriel; Gudmundsson, Sanna; Baxter, Samantha; Seaby, Eleanor G; England, Eleina; Wood, Jordan C; Son, Rachel G; Watts, Nicholas A; Karczewski, Konrad J; Harrison, Steven M; MacArthur, Daniel G; Rehm, Heidi L; O'Donnell-Luria, Anne.
Afiliación
  • Singer-Berk M; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Gudmundsson S; Center for Genomic Medicine & Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Baxter S; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Seaby EG; Center for Genomic Medicine & Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • England E; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • Wood JC; Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden.
  • Son RG; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Watts NA; Center for Genomic Medicine & Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Karczewski KJ; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Harrison SM; Center for Genomic Medicine & Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
  • MacArthur DG; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • Rehm HL; Genomic Informatics Group, University Hospital Southampton, Southampton, United Kingdom.
  • O'Donnell-Luria A; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
medRxiv ; 2023 Mar 09.
Article en En | MEDLINE | ID: mdl-36945502
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: MedRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos