Radio-iBAG: radiomics-based integrative Bayesian analysis of multiplatform genomic data

DOI10.1214/19-AOAS1238zbMath1433.62320WikidataQ102326781 ScholiaQ102326781MaRDI QIDQ2281245

Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Arvind Rao, Youyi Zhang, Shivali Narang Aerry

Publication date: 19 December 2019

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

Full work available at URL: https://projecteuclid.org/euclid.aoas/1571277779

zbMATH Keywords

survivalcancerBayesian modelingsparse principal component analysismulti-scale modelsintegrative modelingmulti-platform genomicsradiological imagingsparsity priors

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Image analysis in multivariate analysis (62H35) Genetics and epigenetics (92D10) Reliability and life testing (62N05)

Related Items

Integrative Bayesian Models Using Post-Selective Inference: A Case Study in Radiogenomics ⋮ Approximate Selective Inference via Maximum Likelihood ⋮ Radio-iBAG: radiomics-based integrative Bayesian analysis of multiplatform genomic data ⋮ Radio-iBAG

Uses Software

• mgcv
• TCGA-assembler
• multiMiR
• iBAG

Cites Work

• Unnamed Item
• Optimal predictive model selection.
• Radio-iBAG: radiomics-based integrative Bayesian analysis of multiplatform genomic data
• Inference with normal-gamma prior distributions in regression problems
• An Integrative Bayesian Modeling Approach to Imaging Genetics
• The horseshoe estimator for sparse signals
• The Bayesian Lasso
• Bayesian Variable Selection in Linear Regression
• Generalized double Pareto shrinkage
• Regularization and Variable Selection Via the Elastic Net
• Dirichlet–Laplace Priors for Optimal Shrinkage