A scalable Bayesian functional GWAS method accounting for multivariate quantitative functional annotations with applications for studying Alzheimer disease

Existing methods for integrating functional annotations in genome-wide association studies (GWASs) to fine-map and prioritize potential causal variants are limited to using non-overlapped categorical annotations or limited by the computation burden of modeling genome-wide variants. To overcome these...

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Detalles Bibliográficos
Autores principales: Chen, Junyu, Wang, Lei, De Jager, Philip L., Bennett, David A., Buchman, Aron S., Yang, Jingjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530673/
https://www.ncbi.nlm.nih.gov/pubmed/36204489
http://dx.doi.org/10.1016/j.xhgg.2022.100143

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530673/
https://www.ncbi.nlm.nih.gov/pubmed/36204489
http://dx.doi.org/10.1016/j.xhgg.2022.100143

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