| --- |
| language: |
| - en |
| - zh |
| license: other |
| task_categories: |
| - feature-extraction |
| tags: |
| - single-cell |
| - transcriptomics |
| - perturbation |
| - drug-response |
| size_categories: |
| - 10K<n<100K |
| pretty_name: Curated Single-Cell Drug Perturbation Benchmarks |
| --- |
| |
| # Curated Single-Cell Drug Perturbation Benchmarks |
|
|
| This release contains 20 single-cell drug-perturbation benchmarks linked to 20 distinct papers. Each benchmark includes one control expression matrix, one treated ground-truth matrix, and a JSON test specification. The selection prioritizes broad target-gene panels and agreement between the encoded target directions and the main conclusions of the source paper. |
|
|
| ## Release status and license |
|
|
| The benchmark metadata is prepared for release, but redistribution rights for the derived H5AD files must be confirmed from the original studies before making the repository public. `license: other` is intentionally conservative and does not grant rights beyond those of the source datasets. Users remain responsible for complying with the original study terms and citing the corresponding paper. |
|
|
| ## Files |
|
|
| ```text |
| README.md |
| benchmarks.csv |
| release_manifest.csv |
| release_audit.json |
| data/ |
| <benchmark_id>/ |
| control.h5ad |
| ground_truth.h5ad |
| test_case.json |
| ``` |
|
|
| The 60 core data files total 30.4 GiB. `release_manifest.csv` records the exact byte size and SHA256 digest of each file. Local source paths are excluded from the public manifest. |
|
|
| ## Benchmarks |
|
|
| | Rank | Benchmark | PMID | Perturbation | Tissue | Targets | Direction agreement | |
| |---:|---|---:|---|---|---:|---:| |
| | 1 | `38937474_01` | 38937474 | osimertinib | Lung | 34 | 32/34 (94.1%) | |
| | 2 | `38895265_01` | 38895265 | Paclitaxel | Breast | 18 | 18/18 (100.0%) | |
| | 3 | `34591417_01` | 34591417 | vemurafenib | Skin | 14 | 14/14 (100.0%) | |
| | 4 | `40766395_01` | 40766395 | Brefeldin A | Liver | 14 | 14/14 (100.0%) | |
| | 5 | `37086265_01` | 37086265 | etoposide | Lung | 18 | 16/18 (88.9%) | |
| | 6 | `33712615_01` | 33712615 | erlotinib | Lung | 19 | 15/19 (78.9%) | |
| | 7 | `32846134_01` | 32846134 | 5-fluorouracil | Colon | 9 | 9/9 (100.0%) | |
| | 8 | `37732484_01` | 37732484 | paclitaxel | Aorta | 11 | 10/11 (90.9%) | |
| | 9 | `36318267_01` | 36318267 | estradiol | Breast | 8 | 8/8 (100.0%) | |
| | 10 | `36553506_01` | 36553506 | panobinostat | Brain | 12 | 10/12 (83.3%) | |
| | 11 | `35410383_01` | 35410383 | Fluorouracil | Breast | 6 | 6/6 (100.0%) | |
| | 12 | `41871169_01` | 41871169 | panobinostat | B lymphoblast | 6 | 6/6 (100.0%) | |
| | 13 | `38652658_01` | 38652658 | ispinesib | Brain | 9 | 8/9 (88.9%) | |
| | 14 | `36382181_01` | 36382181 | enzalutamide | Prostate | 9 | 7/9 (77.8%) | |
| | 15 | `32094658_01` | 32094658 | latrunculin A | Pancreas | 4 | 4/4 (100.0%) | |
| | 16 | `38272949_02` | 38272949 | GW3965 | Brain | 4 | 4/4 (100.0%) | |
| | 17 | `38589664_01` | 38589664 | cisplatin | Stomach | 3 | 3/3 (100.0%) | |
| | 18 | `39803533_01` | 39803533 | TCDD | Skin | 3 | 3/3 (100.0%) | |
| | 19 | `40166195_01` | 40166195 | doxorubicin | Breast | 3 | 3/3 (100.0%) | |
| | 20 | `34857732_01` | 34857732 | GSK126 | Prostate | 8 | 5/8 (62.5%) | |
|
|
| Across the 20 benchmarks there are 212 within-benchmark unique target genes, of which 195 (92.0%) match the encoded direction under the strict aggregate check described below. |
|
|
| ## Direction validation |
|
|
| For each target gene, the release audit compares the mean of the treated matrix (`ground_truth.h5ad`) with the mean of the control matrix (`control.h5ad`): |
|
|
| ```text |
| relative_effect = (treated_mean - control_mean) / |
| (abs(treated_mean) + abs(control_mean)) |
| ``` |
|
|
| Values at least `0.1` are classified as `UP`, values at most `-0.1` as `DOWN`, and intermediate values as `NS`. This is an aggregate dataset-level consistency check, not a dose-stratified or time-stratified statistical significance test. |
|
|
| ## H5AD content |
|
|
| `X` contains the processed expression matrix. The files also retain observation and variable metadata and, where available, a `counts` layer. Consult `test_case.json` for target genes, expected relation, perturbation groups, time groups, and cell type for each test. |
|
|
| ## Audit notes |
|
|
| All hard integrity checks passed. Two JSON test cases contain no target genes and are therefore not evaluable. Several JSON time/dose labels are not present as literal categorical values in `obs`; use the recorded `condition`, `orig.ident`, and `sample_id` fields together with the JSON specification. One benchmark has six barcodes shared between the separate control and treated files; use `sample_id` or the split name when concatenating. One benchmark stores the same gene set in a different column order between splits; downstream joins must align by `var_names`, never by column position. |
|
|
| ## Data leakage warning |
|
|
| Benchmarks derived from the same source context may not represent statistically independent samples. Keep `benchmark_id` and PMID grouping intact when constructing train/test splits; random cell-level splitting can cause leakage. |
|
|
| ## Citation |
|
|
| Each row in `benchmarks.csv` contains the PMID and paper title. Cite the relevant original papers when using individual benchmarks. |
|
|