PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.
Authors
Raven, Kathy E
Publication Date
2022-03-25Journal Title
Commun Biol
ISSN
2399-3642
Publisher
Springer Science and Business Media LLC
Volume
5
Issue
1
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Coll, F., Gouliouris, T., Bruchmann, S., Phelan, J., Raven, K. E., Clark, T. G., Parkhill, J., & et al. (2022). PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.. Commun Biol, 5 (1) https://doi.org/10.1038/s42003-022-03194-2
Abstract
Genome-wide association studies (GWAS) are increasingly being applied to investigate the genetic basis of bacterial traits. However, approaches to perform power calculations for bacterial GWAS are limited. Here we implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. First, a sub-sampling approach was undertaken to reduce the allele frequency and effect size of a known and detectable genotype-phenotype relationship by modifying phenotype labels. Second, a phenotype-simulation approach was conducted to simulate phenotypes from existing genetic variants. We implemented both approaches into a computational pipeline (PowerBacGWAS) that supports power calculations for burden testing, pan-genome and variant GWAS; and applied it to collections of Enterococcus faecium, Klebsiella pneumoniae and Mycobacterium tuberculosis. We used this pipeline to determine sample sizes required to detect causal variants of different minor allele frequencies (MAF), effect sizes and phenotype heritability, and studied the effect of homoplasy and population diversity on the power to detect causal variants. Our pipeline and user documentation are made available and can be applied to other bacterial populations. PowerBacGWAS can be used to determine sample sizes required to find statistically significant associations, or the associations detectable with a given sample size. We recommend to perform power calculations using existing genomes of the bacterial species and population of study.
Keywords
Article, /631/326/325/2482, /631/208/325/2482, /631/114/2785, /45/43, /38/23, article
Sponsorship
Wellcome Trust (Wellcome) (201344/Z/16/Z)
Identifiers
s42003-022-03194-2, 3194
External DOI: https://doi.org/10.1038/s42003-022-03194-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335586
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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