PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.
PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.
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DOI：
10.1038/s42003-022-03194-2
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发表时间：
2022-03-25
影响因子：
5.9
通讯作者：
Peacock SJ
中科院分区：
文献类型：
--
作者：
Coll F;Gouliouris T;Bruchmann S;Phelan J;Raven KE;Clark TG;Parkhill J;Peacock SJ
全基因组关联研究（GWAS）越来越多地应用于研究细菌性状的遗传基础。然而，进行细菌GWAS功率计算的方法是有限的。在这里，我们实施了两种替代方法来使用现有的细菌基因组集合进行功率计算。首先，采用子抽样方法，通过修改表型标记来降低已知和可检测的基因型-表型关系的等位基因频率和效应大小。其次，采用表型模拟方法模拟现有遗传变异的表型。我们将这两种方法实现到一个计算管道（PowerBacGWAS）中，该管道支持负荷测试、泛基因组和变体GWAS的功率计算；并将其应用于粪肠球菌、肺炎克雷伯菌和结核分枝杆菌的采集。我们使用这个管道来确定检测不同次要等位基因频率（MAF）因果变异所需的样本量、效应大小和表型遗传力，并研究同质性和群体多样性对检测因果变异能力的影响。Our管道和用户文档可用，并可应用于其他细菌种群。PowerBacGWAS可用于确定所需的样本量，以发现统计上显著的关联，或在给定样本量下可检测到的关联。我们建议使用所研究的细菌种类和种群的现有基因组进行功率计算。PowerBacGWAS是一个计算管道，它使用现有的基因组数据来执行细菌全基因组关联研究的功率计算。
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. PowerBacGWAS is a computational pipeline that uses existing genomic data to perform power calculations for bacterial genome-wide association studies.
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影响因子：
4.5
作者：
Chewapreecha C;Marttinen P;Croucher NJ;Salter SJ;Harris SR;Mather AE;Hanage WP;Goldblatt D;Nosten FH;Turner C;Turner P;Bentley SD;Parkhill J
通讯作者：
Parkhill J
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3.9
作者：
Bush SJ
通讯作者：
Bush SJ
影响因子：
3.9
作者：
Lees JA;Kremer PHC;Manso AS;Croucher NJ;Ferwerda B;Serón MV;Oggioni MR;Parkhill J;Brouwer MC;van der Ende A;van de Beek D;Bentley SD
通讯作者：
Bentley SD
影响因子：
28.3
作者：
Gouliouris T;Coll F;Ludden C;Blane B;Raven KE;Naydenova P;Crawley C;Török ME;Enoch DA;Brown NM;Harrison EM;Parkhill J;Peacock SJ
通讯作者：
Peacock SJ
影响因子：
11.8
作者：
Cremers, Amelieke J. H.;Mobegi, Fredrick M.;de Jonge, Marien I.
通讯作者：
de Jonge, Marien I.