Biostatistics Weekly Seminar

Understanding the relationship between the microbiome and health outcomes often requires investigation of the microbiome across time or in combination with other types of omics data. However, analyzing these data is complicated by the challenges inherent to microbiome data, including high dimensionality, sparsity, compositional constraints, phylogenetic structure, and relationships among bacterial taxa. Appropriate methods to address these issues are still unclear, particularly in the context of longitudinal measurements or integrative omics data. We propose distance-based methods for studying associations between the microbiome across time and outcomes of interest, and demonstrate their utility via both simulation studies and application to two microbiome datasets.

MRBIII, Room 1220
6 November 2019
1:30pm