Differential-expression evaluation compares predicted gene responses against observed differential-expression labels.
Explanatory profile: source reviewed · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Datasets | Cell-type–perturbation combinations with responses available across donors.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Splits | A subset of complete combinations is held out for testing; models are fitted separately for each donor.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Metrics | Gene-expression R-squared is contrasted with precision–recall evaluation of differentially expressed genes.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Baselines | Cell-type-only, perturbation-only and two-factor linear models, plus SI-A.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Leakage controls | Complete cell-type–perturbation combinations are held out. Models are fitted separately for each donor, so this is not an unseen-donor generalization test.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Uncertainty | Figure 6 shows the distribution of AUPRC across 100 held-out cell-type–perturbation pairs and marks their averages. These are between-pair distributions, not confidence intervals for an aggregate score; no such interval is specified in this evaluation passage.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Results: In silico models and evaluation of performance; Figure 6 caption |
| Entity type | Paper-specific computational evaluation protocol.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Organisms | Human peripheral blood mononuclear cells from three healthy donors, measured 24 hours after compound treatment.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Results: DEG prediction on population-level responses under multiple perturbations across multiple cell types |
| Assays | Measured expression responses and differential-expression targets.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Allowed inputs | Cell type, perturbation identity and expression information permitted by the chosen model.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
| Adaptation | Models fit separately per donor with complete cell-type–perturbation combinations held out.SourcesAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Methods: In silico models and evaluation of performance; cached text lines 100–103 |
Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.
Cell-type–perturbation combinations with responses available across donors. A subset of complete combinations is held out for testing; models are fitted separately for each donor. Gene-expression R-squared is contrasted with precision–recall evaluation of differentially expressed genes. Cell-type-only, perturbation-only and two-factor linear models, plus SI-A. Complete cell-type–perturbation combinations are held out. Models are fitted separately for each donor, so this is not an unseen-donor generalization test.
Each evaluation records what was tested and under which conditions.
Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| scGen: differentially expressed gene identification Configuration: scGenTask: differentially expressed gene identificationDataset: stimulated immune PBMC In-silico perturbation assessment with precision sampled at fixed 50% recall Independent external evaluation · Evaluation metadata: needs review | ||
| 0.91 precision at 50% recall Unit: fraction · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedAUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes · Table 3, CD14+Mono section, scGen row, Precision at 50% Recall column Source checking is not independent reproduction. |
Last literature check: 2026-09-17. Primary-paper discovery and source inspection. Source-checked results are not independently reproduced experiments.
| Paper or primary resource | Version | Reference |
|---|---|---|
| AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes | PMC archival version PMC12400816.1 | Read source DOI: 10.1093/bib/bbaf426 |
primary comparison table screened
Targeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change.
Stable record: reported-task-003d746a129c9bTrace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
18 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Input: Cell type, perturbation identity and expression information permitted by the chosen model.","Evaluation: A subset of complete combinations is held out for testing; models are fitted separately for each donor.","Readout: Gene-expression R-squared is contrasted with precision–recall evaluation of differentially expressed genes."] Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Computational evaluation flow Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Datasets Cell-type–perturbation combinations with responses available across donors. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Splits A subset of complete combinations is held out for testing; models are fitted separately for each donor. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Adaptation Models fit separately per donor with complete cell-type–perturbation combinations held out. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Metrics Gene-expression R-squared is contrasted with precision–recall evaluation of differentially expressed genes. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Baselines Cell-type-only, perturbation-only and two-factor linear models, plus SI-A. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Leakage controls Complete cell-type–perturbation combinations are held out. Models are fitted separately for each donor, so this is not an unseen-donor generalization test. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Methods: In silico models and evaluation of performance; cached text lines 100–103 Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Uncertainty Figure 6 shows the distribution of AUPRC across 100 held-out cell-type–perturbation pairs and marks their averages. These are between-pair distributions, not confidence intervals for an aggregate score; no such interval is specified in this evaluation passage. Individual claims | AUPRC: a metric for evaluating the performance of in-silico perturbation methods in identifying differentially expressed genes Results: In silico models and evaluation of performance; Figure 6 caption Version: PMC archival version PMC12400816.1 | source checked automated source review · 2026-09-16 Audit detailsTargeted full-paper and supplement review of the outstanding task fields, with original dataset metadata checked where accessible. Source-scoped omissions are explicit; no independent benchmark reproduction or numerical-result change. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-09-17-d277315f7d76 · Record review: needs review
Stable ID: reported-task-003d746a129c9b