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.
Distribution based nearest neighbor imputation for truncated high dimensional data with applications to pre-clinical and clinical metabolomics studies
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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.