A large, searchable collection of human microbiome data
Human Microbiome Compendium: large-scale curation and processing of human microbiome datasets
This project will gather and standardize over 750,000 human microbiome samples into one searchable resource to help researchers find real links between microbes and health.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project ID | NIH-11144482 on NIH RePORTER |
What this research studies
If you or a family member has a condition linked to microbes, this project will combine and clean hundreds of thousands of publicly available gut, skin, and other microbiome samples so scientists can compare them consistently. The team will use automated pipelines to process both amplicon and shotgun sequencing data, compute relative abundances of microbes in each sample, and attach standardized metadata from sources like the NCBI Sequence Read Archive. By pooling many small, noisy studies into a single compendium, researchers can spot consistent patterns that individual studies miss. The platform will be searchable so researchers can compile relevant sample sets for new analyses.
Who could benefit from this research
Good fit: People with conditions often linked to the microbiome—such as inflammatory bowel disease, obesity, allergies, or recurrent infections—are most likely to benefit or be future candidates for related studies.
Not a fit: People with acute conditions needing immediate treatment or diseases with no known microbial connection may not see direct benefits from this data-focused project.
Why it matters
Potential benefit: If successful, this resource could speed development of more reliable microbiome-based diagnostics and treatments by revealing consistent microbial signals across large datasets.
How similar studies have performed: Smaller public microbiome collections and re-analyses have produced useful disease leads, but this automated project is larger and aims to reveal signals hidden in prior noise.
Where this research is happening
Chicago, United States
- University of Chicago — Chicago, United States (Active)
Researchers
- Principal investigator: Blekhman, Ran — University of Chicago
- Study coordinator: Blekhman, Ran
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.