bGWAS: an R package to perform Bayesian genome wide association studies.

Détails

Ressource 1Télécharger: 32470106_BIB_01E6A249C073.pdf (242.73 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY-NC 4.0
ID Serval
serval:BIB_01E6A249C073
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
bGWAS: an R package to perform Bayesian genome wide association studies.
Périodique
Bioinformatics
Auteur(s)
Mounier N., Kutalik Z.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
01/08/2020
Peer-reviewed
Oui
Volume
36
Numéro
15
Pages
4374-4376
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms.
bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS.
Supplementary data are available at Bioinformatics online.
Pubmed
Open Access
Oui
Création de la notice
10/06/2020 21:43
Dernière modification de la notice
15/01/2021 8:08
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