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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Microbiology Society
2020
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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. |
format | Online Article Text |
id | pubmed-7725327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Microbiology Society |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT saundkatie hogwashthreemethodsforgenomewideassociationstudiesinbacteria AT snitkinevans hogwashthreemethodsforgenomewideassociationstudiesinbacteria |