A Bayesian graphical model for genome-wide association studies (GWAS)

DOI10.1214/16-AOAS909zbMath1400.62251OpenAlexW2492804687MaRDI QIDQ312923

Jinnan Liu, Matt Friedlander, Hilmi Ozcelik, Laurent Briollais, Adrian Dobra, Hélène Massam

Publication date: 9 September 2016

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1469199893

zbMATH Keywords

breast cancerBayesianstochastic searchgraphical modelSNPGWAS

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Protein sequences, DNA sequences (92D20) Contingency tables (62H17)

Related Items

Bayesian inference of clustering and multiple Gaussian graphical models selection, genMOSS

Uses Software

• R
• PLINK
• Haploview
• pi-MASS
• MaCH
• Eigenstrat

Cites Work

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• Bayesian variable selection regression for genome-wide association studies and other large-scale problems
• Bayes factors and the geometry of discrete hierarchical loglinear models
• The mode oriented stochastic search (MOSS) algorithm for log-linear models with conjugate priors
• Bayesian model search and multilevel inference for SNP association studies
• A conjugate prior for discrete hierarchical log-linear models
• A fast procedure for model search in multidimensional contingency tables
• Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models