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NGSphy: phylogenomic simulation of next-generation sequencing data.
Escalona, Merly; Rocha, Sara; Posada, David.
Afiliação
  • Escalona M; Department of Biochemistry, Genetics and Immunology.
  • Rocha S; Department of Biochemistry, Genetics and Immunology.
  • Posada D; Department of Biochemistry, Genetics and Immunology.
Bioinformatics ; 34(14): 2506-2507, 2018 07 15.
Article em En | MEDLINE | ID: mdl-29534152
ABSTRACT
Motivation Advances in sequencing technologies have made it feasible to obtain massive datasets for phylogenomic inference, often consisting of large numbers of loci from multiple species and individuals. The phylogenomic analysis of next-generation sequencing (NGS) data requires a complex computational pipeline where multiple technical and methodological decisions are necessary that can influence the final tree obtained, like those related to coverage, assembly, mapping, variant calling and/or phasing.

Results:

To assess the influence of these variables we introduce NGSphy, an open-source tool for the simulation of Illumina reads/read counts obtained from haploid/diploid individual genomes with thousands of independent gene families evolving under a common species tree. In order to resemble real NGS experiments, NGSphy includes multiple options to model sequencing coverage (depth) heterogeneity across species, individuals and loci, including off-target or uncaptured loci. For comprehensive simulations covering multiple evolutionary scenarios, parameter values for the different replicates can be sampled from user-defined statistical distributions. Availability and implementation Source code, full documentation and tutorials including a 'Getting started' guide are available at http//github.com/merlyescalona/ngsphy. Supplementary information Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Simulação por Computador / Software / Genoma / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Simulação por Computador / Software / Genoma / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2018 Tipo de documento: Article