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G2GSnake: a Snakemake workflow for host-pathogen genomic association studies.
Xu, Zhi Ming; Naret, Olivier; Oumelloul, Mariam Ait; Fellay, Jacques.
Afiliación
  • Xu ZM; School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
  • Naret O; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.
  • Oumelloul MA; School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland.
  • Fellay J; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.
Bioinform Adv ; 3(1): vbad142, 2023.
Article en En | MEDLINE | ID: mdl-37840906
ABSTRACT

Summary:

Joint analyses of paired host and pathogen genome sequences have the potential to enhance our understanding of host-pathogen interactions. A systematic approach to conduct such a joint analysis is through a "genome-to-genome" (G2G) association study, which involves testing for associations between all host and pathogen genetic variants. Significant associations reveal host genetic factors that might drive pathogen variation, highlighting biological mechanisms likely to be involved in host control and pathogen escape. Here, we present a Snakemake workflow that allows researchers to conduct G2G studies in a reproducible and scalable manner. In addition, we have developed an intuitive R Shiny application that generates custom summaries of the results, enabling users to derive relevant insights. Availability and implementation G2GSnake is freely available at https//github.com/zmx21/G2GSnake under the MIT license.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Bioinform Adv Año: 2023 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Bioinform Adv Año: 2023 Tipo del documento: Article País de afiliación: Suiza
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