Humans are host to thousands of species of microbes. They naturally live on our skin, in our gut,
mouth, and a number of other sites. The full impact of these diverse microbiota on human health
is not completely understood, but results obtained over the last several years indicate that the
dynamic relationship between host and microbiota plays a far more integral role than previously thought.
Scientists are eager to explore how the microbiome influences human health, including conditions
like auto-immune disease, depression, malnutrition, and diabetes.
Learn more about the microbiome here.
The first phase of the Human Microbiome Project (HMP), funded by the NIH Common Fund,
generated over 20 terabytes of metagenomic data. Five sites (nasal passages, oral cavity, skin,
gastrointestinal tract, and urogenital tract) in healthy individuals were sampled for whole
genome and 16S rRNA sequencing to characterize the commensal microbiota present in the human body.
The second phase, referred to as the Integrative Human Microbiome Project (iHMP), aims to generate data and analytical resources to permit comprehensive characterization of how the microbiome impacts human health and disease. The iHMP dataset contains longitudinal information from host and microbiome, including metagenomic, metatranscriptomic, human genetic, microbial culture, and other data types from each cohort study in the project.
Mining these datasets offers great promise for therapeutic targets as well as for identifying molecular signatures for health and disease. However, the assembly and analysis of metagenomics data remains challenging for many researchers, who may not have access to the significant computing resources required.
Users all over the world can now access 13 TB of microbiome study results and conduct their own data analysis directly. The Human Microbiome Project has made data from both of its phases available through its data portal: https://portal.hmpdacc.org. In addition, 16S data from the HMP can be found among AWS Public Data Sets and analyzed through an AWS EC2 account.