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nf-gwas-pipeline: A Nextflow Genome-Wide Association Study Pipeline.
Song, Zeyuan; Gurinovich, Anastasia; Federico, Anthony; Monti, Stefano; Sebastiani, Paola.
Afiliação
  • Song Z; Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02218, USA.
  • Gurinovich A; Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02218, USA.
  • Federico A; Section of Computational Biomedicine, Boston University School of Medicine, 72 East Concord St., Boston, MA 02218, USA.
  • Monti S; Bioinformatics Program, Boston University, 24 Cummington Mall, Boston, MA 02215, USA.
  • Sebastiani P; Section of Computational Biomedicine, Boston University School of Medicine, 72 East Concord St., Boston, MA 02218, USA.
Article em En | MEDLINE | ID: mdl-35647481
ABSTRACT
A tool for conducting Genome-Wide Association Study (GWAS) in a systematic, automated and reproducible manner is overdue. We developed an automated GWAS pipeline by combining multiple analysis tools - including bcftools, vcftools, the R packages SNPRelate/GENESIS/GMMAT and ANNOVAR - through Nextflow, which is a portable, flexible, and reproducible reactive workflow framework for developing pipelines. The GWAS pipeline integrates the steps of data quality control and assessment and genetic association analyses, including analysis of cross-sectional and longitudinal studies with either single variants or gene-based tests, into a unified analysis workflow. The pipeline is implemented in Nextflow, dependencies are distributed through Docker, and the code is publicly available on Github.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article