Statistical analyses of multidomain data for the microbiome

Longitudinal studies using perturbations enable us to study the resilience of the human microbiome. These are particularly informative in the case of antibiotic courses and colonic clean-out. The heterogeneity of the sources of information (time, phylogenetic trees, community networks, samples, batches, noise levels, sequences) pose real visualization and analytic challenges that we have overcome using interactive multivariate mappings. These enable simple tree-aware projections and account for uncertainties using Bayesian MCMC implementations.

Date:

October 13, 2017

Haut-parleurs:

Susan Homes

Affiliation:

Stanford University