Count matrix analysis - application to molecular microbial data


Differential topic analysis

In microbiome research, an important goal is often to find taxonomic differences across environments or groups. We introduce differential topic analysis that facilitates inferences on latent microbial communities.

DNA contamination removal in molecular microbial studies

Molecular technologies can quantify bacteria in low biomass samples, such as blood. However, DNA contamination from external sources misidentifies the taxon’s provenance. We developed a Bayesian reference analysis to infer DNA contamination.

Inference on longitudinal microbiome data

Longitudinal designs help experimenters overcome some of the difficulties caused by the temporal and subject-to-subject variability of the microbiome. They also allow subjects to be used as their own controls.

The proposed resampling method combined moving block bootstrap (MBB) method, empirical subsampling method, mixture model, generalized linear model, generalized estimating equation, median-ratio method, and shrinkage estimation to enabling inference on microbiome longitudinal data. With the optimal block size computed using subsampling, the MBB method accounts for within-subject dependency by using overlapping blocks of repeated observations within each subject to draw valid inferences based on approximately pivotal statistic.



  • In progress…



  • Identify deferentially abundant taxa in preterm and term labor (vaginal microbiome data).