Identifying pleiotropic genes via the composite test amidst the complexity of polygenic traits.
Brief Bioinform
; 25(4)2024 May 23.
Article
em En
| MEDLINE
| ID: mdl-39007593
ABSTRACT
Identifying the causal relationship between genotype and phenotype is essential to expanding our understanding of the gene regulatory network spanning the molecular level to perceptible traits. A pleiotropic gene can act as a central hub in the network, influencing multiple outcomes. Identifying such a gene involves testing under a composite null hypothesis where the gene is associated with, at most, one trait. Traditional methods such as meta-analyses of top-hit $P$-values and sequential testing of multiple traits have been proposed, but these methods fail to consider the background of genome-wide signals. Since Huang's composite test produces uniformly distributed $P$-values for genome-wide variants under the composite null, we propose a gene-level pleiotropy test that entails combining the aforementioned method with the aggregated Cauchy association test. A polygenic trait involves multiple genes with different functions to co-regulate mechanisms. We show that polygenicity should be considered when identifying pleiotropic genes; otherwise, the associations polygenic traits initiate will give rise to false positives. In this study, we constructed gene-trait functional modules using the results of the proposed pleiotropy tests. Our analysis suite was implemented as an R package PGCtest. We demonstrated the proposed method with an application study of the Taiwan Biobank database and identified functional modules comprising specific genes and their co-regulated traits.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Herança Multifatorial
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Estudo de Associação Genômica Ampla
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Pleiotropia Genética
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article