Data Science and Informatics for Panomic Microbiome Discoveries

Synopsis: Microbiome is a term used to describe the collection of all microorganisms that colonize our bodies. Whereas understanding the human genome has received enormous amount of attention in the last 20 years, the impact of host associated microbiome genomes (the metagenome) and their function in human health and disease is still in very early stages of being conceptualized. The recent surge in microbiome science has been afforded by increasing availability of technologies, such as high-throughput DNA sequencing, mass spectrometry, automated cell sorting, etc. Most notably, of course, the ability to sequence hundreds of individual microbiomes in a single run of a sequencing instrument has resulted in a perfect storm of microbial community profiling datasets addressing a vast array of biomedical questions. This presentation will motivate the need for microbiome specific data analytic techniques. I will highlight a few promising analytic approaches and elements of a general framework for integrating high dimensional host-microbiome data. I will also describe how informatics can accelerate microbiome research by simplifying research access to human microbiome specimens from clinically relevant patient populations via a Living µBiome Bank.