You have a hypothesis.
Search 50,000+ pre-processed spatial samples. Find new targets, build virtual cohorts and test ideas before you generate new data.
- 01In silico target discovery
- 02Virtual cohorts
- 03Context for your pilot data
The spatial map of human biology
Search it. Zoom in. Find your way. Now for human tissue. We turn spatial omics data into one navigable atlas, so you can see where disease begins, not only what it expresses.
Trusted by researchers at
Published in Neuron, 2025



Why now
Every spatial experiment charts a small piece of human tissue. Most of those charts sit in separate files, formats and labs. We join them into one map that you can search, compare and zoom, from the whole organism down to a single transcript.
The atlas
Findings are pinned to the place in the body where they happen. Turn the body. Hover or tap a marker to see what is already on the map.
Drag to turn
Every scale
How it works
Search 50,000+ pre-processed spatial samples. Find new targets, build virtual cohorts and test ideas before you generate new data.
Hand us raw data. Our end-to-end engine charts it and returns publication-ready results, fully reproducible.
Use cases
Mine the atlas for spatial biomarkers and therapeutic targets.
Assemble disease cohorts from existing data. No wet lab, no waiting.
Compare your first slides against thousands of reference samples.
Map immune niches and exhaustion at subcellular resolution.
Place rare cell states inside lesions across many donors.
Figures, interactive reports and queryable data objects.
Results
We partnered with Cambridge to process fragmented spatial cohorts from post-mortem brain tissues at scale. The result: identification of Disease-Associated Radial Glia-like cells in chronic MS lesions.
“By scaling this spatial analysis, we successfully identified DARGs in chronic active lesions - uncovering a novel cellular axis for disease pathobiology and potential therapeutic intervention.”
We partnered with SOTIO Biotech to process complex Xenium spatial cohorts comparing cervical and head and neck cancers. The result: identifying dense regulatory T cell populations and localized exhaustion signatures as key drivers of immunosuppression in cervical cancer.
“Generating the spatial data was only the first step. Carta Genum provided the dedicated bioinformatics capacity we needed, turning our complex datasets into clear, publication-ready biological insights.”
We work with a small number of labs at a time. Let's see if we're a fit.


