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Identifying patients and assessing variant pathogenicity for an autosomal dominant disease-driving gene.
Lee, Winston; de Prisco, Nicola; Gennarino, Vincenzo A.
Afiliação
  • Lee W; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA.
  • de Prisco N; Department of Ophthalmology, Columbia University Irving Medical Center, New York, NY 10032, USA.
  • Gennarino VA; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY 10032, USA.
STAR Protoc ; 3(1): 101150, 2022 03 18.
Article em En | MEDLINE | ID: mdl-35146449
ABSTRACT
Identifying a disease gene and determining its causality in patients can be challenging. Here, we present an approach to predicting the pathogenicity of deletions and missense variants for an autosomal dominant gene. We provide online resources for identifying patients and determining constraint metrics to isolate the causal gene among several candidates encompassed in a shared region of deletion. We also provide instructions for optimizing functional annotation programs that may be otherwise inaccessible to a nonexpert or novice in computational approaches. For complete details on the use and execution of this protocol, please refer to Gennarino et al. (2018).
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Genes Dominantes / Doenças Genéticas Inatas Limite: Humans Idioma: En Revista: STAR Protoc Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Genes Dominantes / Doenças Genéticas Inatas Limite: Humans Idioma: En Revista: STAR Protoc Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos