Join
Two-dimensional embeddings for single-cell visualisation
Embed single-cell expression data in two dimensions while preserving neighbourhoods, distances and densities.
| 1 | { |
| 2 | "domain": "life-health", |
| 3 | "topics": [ |
| 4 | "single-cell" |
| 5 | ], |
| 6 | "type": "algorithm", |
| 7 | "benchmark": { |
| 8 | "task": "Reduce scRNA-seq data to a 2D embedding for visualisation", |
| 9 | "metric": { |
| 10 | "name": "Overall: mean control-scaled metric score (0–1)", |
| 11 | "better": "higher" |
| 12 | }, |
| 13 | "baseline": { |
| 14 | "name": "Best on Open Problems v1.0.0 (densMAP)", |
| 15 | "score": 0.355439 |
| 16 | } |
| 17 | }, |
| 18 | "source": { |
| 19 | "key": "openproblems-bio", |
| 20 | "name": "Open Problems in Single-Cell Analysis", |
| 21 | "url": "https://openproblems.bio/benchmarks/dimensionality_reduction", |
| 22 | "id": "dimensionality_reduction", |
| 23 | "curator": "Open Problems in Single-Cell Analysis consortium", |
| 24 | "poser": "Luke Zappia, Michael Vinyard, Michal Klein et al.", |
| 25 | "status": "open", |
| 26 | "as_of": "2026-10-20", |
| 27 | "catalog": "0521c19bbd38" |
| 28 | } |
| 29 | } |