A Bayesian sparse regression method integrates microbiome and metabolome data by modeling dual missingness mechanisms and compositional priors, with demonstrations on simulated data for imputation and predictor selection plus application to colorectal cancer samples.
Variable selection in regression with compositional covariates
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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q2-classo and q2-gglasso are QIIME 2 plugins that implement sparse log-contrast regression/classification and graphical lasso-based network estimation for microbial compositional data.
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Bayesian Sparse Regression for Microbiome-Metabolite Data Integration
A Bayesian sparse regression method integrates microbiome and metabolome data by modeling dual missingness mechanisms and compositional priors, with demonstrations on simulated data for imputation and predictor selection plus application to colorectal cancer samples.
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Sparse regression, classification, and microbial network estimation in QIIME2 with q2-classo and q2-gglasso
q2-classo and q2-gglasso are QIIME 2 plugins that implement sparse log-contrast regression/classification and graphical lasso-based network estimation for microbial compositional data.