Your browser doesn't support javascript.
loading
Analysis of DNA sequence variants detected by high-throughput sequencing.
Adams, David R; Sincan, Murat; Fuentes Fajardo, Karin; Mullikin, James C; Pierson, Tyler M; Toro, Camilo; Boerkoel, Cornelius F; Tifft, Cynthia J; Gahl, William A; Markello, Tom C.
Afiliação
  • Adams DR; NIH Undiagnosed Diseases Program, NIH, Bethesda, Maryland, USA. david.adams@nih.gov
Hum Mutat ; 33(4): 599-608, 2012 Apr.
Article em En | MEDLINE | ID: mdl-22290882
ABSTRACT
The Undiagnosed Diseases Program at the National Institutes of Health uses high-throughput sequencing (HTS) to diagnose rare and novel diseases. HTS techniques generate large numbers of DNA sequence variants, which must be analyzed and filtered to find candidates for disease causation. Despite the publication of an increasing number of successful exome-based projects, there has been little formal discussion of the analytic steps applied to HTS variant lists. We present the results of our experience with over 30 families for whom HTS sequencing was used in an attempt to find clinical diagnoses. For each family, exome sequence was augmented with high-density SNP-array data. We present a discussion of the theory and practical application of each analytic step and provide example data to illustrate our approach. The article is designed to provide an analytic roadmap for variant analysis, thereby enabling a wide range of researchers and clinical genetics practitioners to perform direct analysis of HTS data for their patients and projects.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Sequenciamento de Nucleotídeos em Larga Escala / Doenças Genéticas Inatas Limite: Humans Idioma: En Revista: Hum Mutat Assunto da revista: GENETICA MEDICA Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Sequenciamento de Nucleotídeos em Larga Escala / Doenças Genéticas Inatas Limite: Humans Idioma: En Revista: Hum Mutat Assunto da revista: GENETICA MEDICA Ano de publicação: 2012 Tipo de documento: Article País de afiliação: Estados Unidos