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

Chen, J., Wang, L., De Jager, P. L., Bennett, D. A., Buchman, A. S., & Yang, J. (2022). A scalable Bayesian functional GWAS method accounting for multivariate quantitative functional annotations with applications for studying Alzheimer disease. Human Genetics and Genomics Advances, 3(4), 100143. https://doi.org/10.1016/j.xhgg.2022.100143
Authors:
Junyu Chen
Lei Wang
Philip L. De Jager
David A. Bennett
Aron S. Buchman
Jingjing Yang
Affiliated Authors:
Philip L. De Jager
Columbia Affiliation:
Author Keywords:
alzheimer disease
bayesian hierarchical variable selection regression
fine-mapping
genome-wide association study
molecular quantitative trait loci
polygenic risk score
quantitative functional annotation
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Publication Type:
Article
Unique ID:
10.1016/j.xhgg.2022.100143
DOI:
10.1016/j.xhgg.2022.100143
Journal:
Human Genetics and Genomics Advances
Publication Date:
Data Source:
Scopus
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