---
pretty_name: PRIMO blind benchmark inputs
license: other
---

# PRIMO public inputs

Blind expression inputs for the PRIMO patient-representation benchmark.
`datasets.yaml` lists opaque ids, modalities, paths, and dimensions; clinical
targets, provenance, donor ids, and cohort metadata remain private.

Each `<dataset_id>/expression.h5ad` stores raw counts in `X`, NCBI Gene IDs in
`var_names`, and symbols in `var["gene_symbols"]`.

- Bulk RNA files have samples as rows and opaque sample ids in `obs_names`.
- Single-cell RNA files are sparse and have cells as rows. Cell ids in
  `obs_names` are opaque. Their only `obs` column is `sample_id`, an opaque
  collection-sample id shared by cells from the same prediction unit.

Each submission covers one selected modality. Submissions are sample-level:
produce one embedding per unique `obs["sample_id"]`, with repeated collection
timepoints kept separate.

The standalone quickstart in the
[PRIMO evaluator Space](https://huggingface.co/spaces/PRIMOmics/primo-eval/blob/main/quickstart.py)
shows the modality-specific download and submission flow. Its single-cell example
applies per-cell
`log2(CP10K + 1)`, mean-pools by `sample_id`, then runs sample-level PCA.