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Detecting viral sequences in NGS data.
Cantalupo, Paul G; Pipas, James M.
Afiliação
  • Cantalupo PG; Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.
  • Pipas JM; Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA. Electronic address: pipas@pitt.edu.
Curr Opin Virol ; 39: 41-48, 2019 12.
Article em En | MEDLINE | ID: mdl-31465960
Next generation sequencing (NGS) technologies provide an increasingly important avenue for detecting known viruses, and for discovering novel viruses present in clinical or environmental samples. Several computational pipelines capable of identifying and classifying viral sequences in NGS data have been developed and used to search for viruses in human or animal samples, microbiomes, and in various environments. In this review we summarize the different approaches used to determine viral presence in sequence data. Strategies for avoiding confounding factors such as physical contamination and computational artifacts that lead to false virus identification are discussed. The application of these methodologies to cancer data sets has led to important insights on viruses both as drivers of and biomarkers for specific tumors.
Assuntos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Vírus / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Curr Opin Virol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Assunto principal: Vírus / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Limite: Animals / Humans Idioma: En Revista: Curr Opin Virol Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Estados Unidos