Compositional Graphical Lasso Resolves the Impact of Parasitic Infection on Gut Microbial Interaction Networks in a Zebrafish Model

DOI10.1080/01621459.2022.2164287arXiv2207.00984MaRDI QIDQ6077536

Duo Jiang, Chuan Tian, Unnamed Author, Yuan Jiang, Unnamed Author

Publication date: 18 October 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2207.00984

zbMATH Keywords

heteroscedasticityparasite infectionadditive log-ratio transformationlogistic normal multinomial distribution

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Sparse inverse covariance estimation with the graphical lasso
• High-dimensional graphs and variable selection with the Lasso
• Minimization of functions having Lipschitz continuous first partial derivatives
• Model selection and estimation in the Gaussian graphical model
• Statistical Interpretation of Species Composition
• The huge Package for High-dimensional Undirected Graph Estimation in R
• A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis
• Convergence of a block coordinate descent method for nondifferentiable minimization
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