Sparse latent factor regression models for genome-wide and epigenome-wide association studies

DOI10.1101/2020.02.07.938381zbMath1494.92066OpenAlexW4221053890MaRDI QIDQ2162483

Basile Jumentier, Johanna Lepeule, Kevin Caye, Barbara Heude, Olivier Francois

Publication date: 8 August 2022

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/sagmb-2021-0035

zbMATH Keywords

statistical methodsgenome-wide associationconfounding factorssparse modelepigenome-wide association

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10)

Uses Software

• glmnet
• qvalue
• Eigenstrat
• Naturalgwas
• lfmm
• GWAS Catalog

Cites Work

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• Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
• Bi-cross-validation for factor analysis
• Confounder adjustment in multiple hypothesis testing
• Pathwise coordinate optimization
• Asymptotic Conditional Singular Value Decomposition for High-Dimensional Genomic Data
• Genomic Control for Association Studies
• An improved and explicit surrogate variable analysis procedure by coefficient adjustment
• Robust reduced-rank regression
• Low-Rank Optimization with Trace Norm Penalty
• High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
• Large-Scale Simultaneous Hypothesis Testing
• Convergence of a block coordinate descent method for nondifferentiable minimization

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