Semiparametric Bayesian variable selection for gene-environment interactions

DOI10.1002/SIM.8434zbMATH Open1546.62619MaRDI QIDQ6627474

Fei Zhou, Xiaoxi Li, Qi Chen, Shuangge Ma, Jie Ren, Cen Wu, Hongmei Zhang, Yunping Jiang

Publication date: 29 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

MCMCBayesian variable selectionsemiparametric modelinghigh-dimensional genomic datagene-environment interactions

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Bayesian variable selection and estimation for group Lasso
• Bayesian group Lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies
• Additive varying-coefficient model for nonlinear gene-environment interactions
• Inference from iterative simulation using multiple sequences
• Optimal predictive model selection.
• Bayesian semiparametric analysis for two-phase studies of gene-environment interaction
• Penalized regression, standard errors, and Bayesian Lassos
• Model selection for Cox models with time-varying coefficients
• Linear or Nonlinear? Automatic Structure Discovery for Partially Linear Models
• A Bayesian Hierarchical Model for Classification with Selection of Functional Predictors
• The Bayesian Lasso
• Varying-coefficient models and basis function approximations for the analysis of repeated measurements
• The Spike-and-Slab LASSO
• Robust gene–environment interaction analysis using penalized trimmed regression
• Varying Index Coefficient Models
• A review of Bayesian variable selection methods: what, how and which
• Penalized integrative semiparametric interaction analysis for multiple genetic datasets
• Bayesian hierarchical structured variable selection methods with application to molecular inversion probe studies in breast cancer

Related Items (3)

Bayesian variable selection for understanding mixtures in environmental exposures ⋮ Gene-gene interaction analysis incorporating network information via a structured Bayesian approach ⋮ BHAFT: Bayesian heredity-constrained accelerated failure time models for detecting gene-environment interactions in survival analysis

This page was built for publication: Semiparametric Bayesian variable selection for gene-environment interactions

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6627474)