Validation

RustScenic validation tracks implementation agreement, runtime, memory and real-data usability against established SCENIC ecosystem outputs where a fair comparison is possible.

The standard is publication-minded: every serious claim should point to a dataset, command, version, hardware context, runtime, memory measurement and output sanity check.

Credibility Snapshot

Signal Evidence
Released package v0.4.7 is the current GitHub release and PyPI package.
Controlled benchmark path validation/head_to_head/head_to_head_summary.json records machine, seed, Python versions, runtime, peak RSS and output signatures.
Lab validation Huang Lab collaborator artefacts include Kamath dopaminergic neurons and 10x human brain GEM-X multiome runs.
Full monolith real-data run Human brain GEM-X v0.4.6 artefact completed GRN, regulons, cisTarget, enhancer links and eRegulons on 8,215 post-QC cells and 123,089 peaks.
Biological sanity check The full monolith human brain run recovered 16 of 17 expected brain TFs.
CI coverage Audit, docs, release and nightly real-data validation workflows keep the public evidence path checked.

Headline Results

Test Result
AUCell vs pySCENIC on Ziegler 2021 airway atlas Mean per-cell Pearson 0.984; 91.7% cells above 0.95.
Canonical airway TF benchmark RustScenic and pySCENIC-unit both recover 8/14; same miss set.
cisTarget AUC kernel vs ctxcore.recovery.aucs Pearson 1.0000; mean absolute difference about 2.4e-5.
Human brain GEM-X SCENIC+ comparison Region-to-gene edge-set Jaccard 1.000; region AUCell mean Pearson 0.823; gene AUCell and eRegulon-edge parity remain weaker.
Real multiome pipeline runs PBMC 3k, mouse brain E18 5k, PBMC granulocyte 10k.
Local unit/integration suite 223 tests passed, 1 skipped in the 2026-05-24 audit.

External Validation

External reports are useful adoption evidence, but they are not used for the headline speedup claim unless they include the same benchmark controls: hardware, command, version, runtime, memory and output signatures.

Tier Dataset Source Evidence Caveat
Committed collaborator adoption artefact Kamath et al. 2022 midbrain dopaminergic neurons issue #68, PR #71, JSON RustScenic 0.4.0 on Google Colab completed GRN plus cisTarget: 266,805 GRN edges, 9 regulons, 174,019 cisTarget rows, 9 of 9 expected DA-neuron TFs recovered. Not a full multiome E2E run. AUCell, enhancer links and eRegulons were out of scope; 3 of 9 regulons had low expression-matrix gene overlap.
Committed collaborator adoption artefact 10x Multiome GEM-X 10k human brain, full monolith run issue #80, JSON RustScenic 0.4.6 completed GRN, regulons, cisTarget, enhancer links and eRegulons on 8,215 post-QC cells and 123,089 peaks: 4,314,539 GRN edges, 108,736 cisTarget rows, 927,002 enhancer links, 16 of 17 expected brain TFs recovered, peak RSS 24.99 GB, total pipeline runtime 54.9 min. Collaborator real-data run, not a SCENIC+ head-to-head row. Used preprocessed ATAC .h5ad; fragments_to_matrix was skipped. Microglial cells were filtered before analysis.
Committed collaborator adoption artefact 10x Multiome GEM-X 10k human brain issue #70, PR #74, JSON RustScenic 0.4.1 completed GRN, AUCell and topics on 8,215 post-QC cells and 123,089 peaks: 4,293,902 GRN edges, 1,748 regulons, peak RSS 9.08 GB. cisTarget, enhancer links and eRegulons were not run. Biological sanity is a top-regulon signal after immune-cell subsetting, not full cell-type enrichment.
Issue-linked report 10x lymphoma 14k issue #69 RustScenic 0.4.1 completed GRN, AUCell and topics on 14,039 post-QC cells; review notes 1,663 regulons and B-cell regulators including POU2F2, PAX5, MEF2B, SPIB, EBF1 and BCL11A. JSON is attached to the issue but not committed in-repo. Low ARI is treated as expected for a mostly homogeneous sample, so this is adoption evidence only.

These rows show the package running outside the maintainer benchmark path. The controlled head-to-head scripts and saved validation artefacts remain the source for public performance claims.

Validation Notes

  • GRN edge rankings are not expected to be bit-identical to arboreto because the implementation uses an independent histogram-GBM path.
  • Downstream cell-level AUCell agreement is stronger than fine-grained GRN edge agreement.
  • Some real-data biological checks currently use expected TF recovery by name; cell-type enrichment checks are part of the next validation tier.
  • The next benchmark tier adds more real multiome datasets, repeated runs and a second machine.

Where To Look