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Zhang et al. propose Bayesian Compositional Generalized Linear Mixed Models (BCGLMM) to enhance disease prediction using microbiome data by accounting for both moderate and minor taxa effects. The model integrates a structured regularized horseshoe prior and a random effect term to effectively capture the phylogenetic relationships among taxa and the cumulative impact of minor contributors. Extensive simulations demonstrate the method

Author

dineshreddygunnam

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EN