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Bayesian Statistical Modeling Of Metagenomics Sequencing Data, Shuang Jiang

Statistical Science Theses and Dissertations

Microbiome count data are high-dimensional and usually suffer from uneven sampling depth, over-dispersion, and zero-inflation. In this thesis, we develop specialized analytical models for analyzing such count data. In Chapter 2, I develop a bi-level Bayesian hierarchical framework for microbiome differential abundance analysis. The bottom level is a multivariate count-generating process that links the observed counts to their latent normalized abundances. The top level is a mixture of Gaussian distributions with a feature selection scheme for differential abundance analysis. A simulation study on both simulated and synthetic data is conducted. A colorectal cancer case study demonstrates that a resulting diagnostic …