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Hogwash: three methods for genome-wide association studies in bacteria

Bacterial genome-wide association studies (bGWAS) capture associations between genomic variation and phenotypic variation. Convergence-based bGWAS methods identify genomic mutations that occur independently multiple times on the phylogenetic tree in the presence of phenotypic variation more often th...

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Detalles Bibliográficos
Autores principales: Saund, Katie, Snitkin, Evan S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725327/
https://www.ncbi.nlm.nih.gov/pubmed/33206035
http://dx.doi.org/10.1099/mgen.0.000469
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author Saund, Katie
Snitkin, Evan S.
author_facet Saund, Katie
Snitkin, Evan S.
author_sort Saund, Katie
collection PubMed
description Bacterial genome-wide association studies (bGWAS) capture associations between genomic variation and phenotypic variation. Convergence-based bGWAS methods identify genomic mutations that occur independently multiple times on the phylogenetic tree in the presence of phenotypic variation more often than is expected by chance. This work introduces hogwash, an open source R package that implements three algorithms for convergence-based bGWAS. Hogwash additionally contains two burden testing approaches to perform gene or pathway analysis to improve power and increase convergence detection for related but weakly penetrant genotypes. To identify optimal use cases, we applied hogwash to data simulated with a variety of phylogenetic signals and convergence distributions. These simulated data are publicly available and contain the relevant metadata regarding convergence and phylogenetic signal for each phenotype and genotype. Hogwash is available for download from GitHub.
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spelling pubmed-77253272020-12-14 Hogwash: three methods for genome-wide association studies in bacteria Saund, Katie Snitkin, Evan S. Microb Genom Method Bacterial genome-wide association studies (bGWAS) capture associations between genomic variation and phenotypic variation. Convergence-based bGWAS methods identify genomic mutations that occur independently multiple times on the phylogenetic tree in the presence of phenotypic variation more often than is expected by chance. This work introduces hogwash, an open source R package that implements three algorithms for convergence-based bGWAS. Hogwash additionally contains two burden testing approaches to perform gene or pathway analysis to improve power and increase convergence detection for related but weakly penetrant genotypes. To identify optimal use cases, we applied hogwash to data simulated with a variety of phylogenetic signals and convergence distributions. These simulated data are publicly available and contain the relevant metadata regarding convergence and phylogenetic signal for each phenotype and genotype. Hogwash is available for download from GitHub. Microbiology Society 2020-11-18 /pmc/articles/PMC7725327/ /pubmed/33206035 http://dx.doi.org/10.1099/mgen.0.000469 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License.
spellingShingle Method
Saund, Katie
Snitkin, Evan S.
Hogwash: three methods for genome-wide association studies in bacteria
title Hogwash: three methods for genome-wide association studies in bacteria
title_full Hogwash: three methods for genome-wide association studies in bacteria
title_fullStr Hogwash: three methods for genome-wide association studies in bacteria
title_full_unstemmed Hogwash: three methods for genome-wide association studies in bacteria
title_short Hogwash: three methods for genome-wide association studies in bacteria
title_sort hogwash: three methods for genome-wide association studies in bacteria
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725327/
https://www.ncbi.nlm.nih.gov/pubmed/33206035
http://dx.doi.org/10.1099/mgen.0.000469
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