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Mining the Unknown: Assigning Function to Noncoding Single Nucleotide Polymorphisms.
Nishizaki, Sierra S; Boyle, Alan P.
Afiliação
  • Nishizaki SS; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
  • Boyle AP; Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: apboyle@umich.edu.
Trends Genet ; 33(1): 34-45, 2017 01.
Article em En | MEDLINE | ID: mdl-27939749
One of the formative goals of genetics research is to understand how genetic variation leads to phenotypic differences and human disease. Genome-wide association studies (GWASs) bring us closer to this goal by linking variation with disease faster than ever before. Despite this, GWASs alone are unable to pinpoint disease-causing single nucleotide polymorphisms (SNPs). Noncoding SNPs, which represent the majority of GWAS SNPs, present a particular challenge. To address this challenge, an array of computational tools designed to prioritize and predict the function of noncoding GWAS SNPs have been developed. However, fewer than 40% of GWAS publications from 2015 utilized these tools. We discuss several leading methods for annotating noncoding variants and how they can be integrated into research pipelines in hopes that they will be broadly applied in future GWAS analyses.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequências Reguladoras de Ácido Nucleico / Biologia Computacional / Polimorfismo de Nucleotídeo Único / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequências Reguladoras de Ácido Nucleico / Biologia Computacional / Polimorfismo de Nucleotídeo Único / Estudo de Associação Genômica Ampla Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article