PhD Defense: Software Infrastructure for Visual and Integrative Analysis of Microbiome Data
Microbiome sequencing allows researchers to reconstruct bacterial community census profiles at resolutions greater than previous methodologies. As a result, increasingly large numbers of these taxonomic community profiles are now generated, analyzed, and published by researchers in the field. In this work, I present new methods and software infrastructure for visualization and sharing of microbiome data. The overall goal is to enable a researcher to complete cycles of exploratory and confirmatory analysis over metagenomic data. I describe Metaviz, an interactive statistical and visual analysis tool specifically designed for effective taxonomic hierarchy navigation and data analysis feature selection. I next detail the incorporation of Metaviz into the Human Microbiome Project Data Portal. I then show a novel method to visualize longitudinal data across multiple features built as an extension over Metaviz. Finally, previous work has shown that specific subjects in an experimental cohort can be identified using their microbiome data. I developed software using a secure multi-party computation library to complete comparative analyses of metagenomic data across cohorts without directly revealing metagenomic feature count values for individuals.
Chair: Dr. Hector Corrada Bravo Dean's rep: Dr. Michael Cummings Members: Dr. Mihai Pop Dr. Niklas Elmqvist Dr. Max Leiserson