Evidence claim
Relevance of Unseen perturbations within a cell line to "Assess models for genetic perturbation experiments"
- Use case
- Assess models for genetic perturbation experiments
- Assessed by
- Sun et al. 2026 unseen-perturbation DE classification (within cell line)
- Relevance
- Proxy evidence
- Endpoint
- Share of gene-perturbation pairs called DE and 3-class DE accuracy by effect-size quantile for held-out perturbations within K562, RPE1, HepG2 and Jurkat, comparing majority vote, KNN and logistic regression baselines with scVI, scGen-based VAE and Scouter
Directly compares simple controls with deep perturbation models on held-out genetic perturbations, scored on the DE calls that guide follow-up experiments. Proxy: DE classification of predicted expression, not experimental hit rates.
40 reviewed evaluations
- 1-NN on Sun et al. 2026 within-cell-line DE classification, four cell lines
- 10-NN on Sun et al. 2026 within-cell-line DE classification, four cell lines
- Logistic regression on Sun et al. 2026 within-cell-line DE classification, four cell lines
- Majority vote on Sun et al. 2026 within-cell-line DE classification, four cell lines
- Scouter on Sun et al. 2026 within-cell-line DE classification, four cell lines
- scVI mean on Sun et al. 2026 within-cell-line DE classification, four cell lines
- scVI sampling on Sun et al. 2026 within-cell-line DE classification, four cell lines
- VAE scGen on Sun et al. 2026 within-cell-line DE classification, four cell lines
- 1-NN on Sun et al. 2026 within-cell-line DE classification, HepG2
- 10-NN on Sun et al. 2026 within-cell-line DE classification, HepG2
- Logistic regression on Sun et al. 2026 within-cell-line DE classification, HepG2
- Majority vote on Sun et al. 2026 within-cell-line DE classification, HepG2
- Scouter on Sun et al. 2026 within-cell-line DE classification, HepG2
- scVI mean on Sun et al. 2026 within-cell-line DE classification, HepG2
- scVI sampling on Sun et al. 2026 within-cell-line DE classification, HepG2
- VAE scGen on Sun et al. 2026 within-cell-line DE classification, HepG2
- 1-NN on Sun et al. 2026 within-cell-line DE classification, Jurkat
- 10-NN on Sun et al. 2026 within-cell-line DE classification, Jurkat
- Logistic regression on Sun et al. 2026 within-cell-line DE classification, Jurkat
- Majority vote on Sun et al. 2026 within-cell-line DE classification, Jurkat
- Scouter on Sun et al. 2026 within-cell-line DE classification, Jurkat
- scVI mean on Sun et al. 2026 within-cell-line DE classification, Jurkat
- scVI sampling on Sun et al. 2026 within-cell-line DE classification, Jurkat
- VAE scGen on Sun et al. 2026 within-cell-line DE classification, Jurkat
- 1-NN on Sun et al. 2026 within-cell-line DE classification, K562
- 10-NN on Sun et al. 2026 within-cell-line DE classification, K562
- Logistic regression on Sun et al. 2026 within-cell-line DE classification, K562
- Majority vote on Sun et al. 2026 within-cell-line DE classification, K562
- Scouter on Sun et al. 2026 within-cell-line DE classification, K562
- scVI mean on Sun et al. 2026 within-cell-line DE classification, K562
- scVI sampling on Sun et al. 2026 within-cell-line DE classification, K562
- VAE scGen on Sun et al. 2026 within-cell-line DE classification, K562
- 1-NN on Sun et al. 2026 within-cell-line DE classification, RPE1
- 10-NN on Sun et al. 2026 within-cell-line DE classification, RPE1
- Logistic regression on Sun et al. 2026 within-cell-line DE classification, RPE1
- Majority vote on Sun et al. 2026 within-cell-line DE classification, RPE1
- Scouter on Sun et al. 2026 within-cell-line DE classification, RPE1
- scVI mean on Sun et al. 2026 within-cell-line DE classification, RPE1
- scVI sampling on Sun et al. 2026 within-cell-line DE classification, RPE1
- VAE scGen on Sun et al. 2026 within-cell-line DE classification, RPE1
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Evidence table
Inspect claims, sources and review details
Trace 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.
19 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
Citation locations1 values
| Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Comparison group sun2026-de-classification Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Comparison title DE classification benchmark (Sun et al. 2026) Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
Constraints2 values
| Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Endpoint Share of gene-perturbation pairs called DE and 3-class DE accuracy by effect-size quantile for held-out perturbations within K562, RPE1, HepG2 and Jurkat, comparing majority vote, KNN and logistic regression baselines with scVI, scGen-based VAE and Scouter Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Claimed field links:assessed_by:lit-cells-networks-20261011-sun2026de-protocol-within-cell-line Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Headline metric accuracy Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
Limitations6 values
| Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
Pinned records123 values
| Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
| Rationale Directly compares simple controls with deep perturbation models on held-out genetic perturbations, scored on the DE calls that guide follow-up experiments. Proxy: DE classification of predicted expression, not experimental hit rates. Context-only references | Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3 Version: bioRxiv preprint version 1, posted 2026-07-24 | not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit detailsField: Source artifact SHA-256: Hash scope: Exact bytes of one download; bioRxiv serves slightly different PDF bytes per download, so the gzip copy in artifacts/ is the reference. |
Sources and history
Release 2026-10-23-5347695500ed · Record review: source checked
1 source record and release history
- Beyond Expression Prediction: Benchmarking Differential Expression Classification in Single-Cell Perturbation Models · Original source · bioRxiv preprint version 1, posted 2026-07-24
Technical metadata and extraction receipts
Stable ID: use-case-mapping-lit-cells-networks-20261011-sun2026de-within-cell-line
- field
- links:assessed_by:lit-cells-networks-20261011-sun2026de-protocol-within-cell-line
- value
- lit-cells-networks-20261011-sun2026de-protocol-within-cell-line
- relevance
- proxy
- endpoint
- Share of gene-perturbation pairs called DE and 3-class DE accuracy by effect-size quantile for held-out perturbations within K562, RPE1, HepG2 and Jurkat, comparing majority vote, KNN and logistic regression baselines with scVI, scGen-based VAE and Scouter
- rationale
- Directly compares simple controls with deep perturbation models on held-out genetic perturbations, scored on the DE calls that guide follow-up experiments. Proxy: DE classification of predicted expression, not experimental hit rates.
- constraints
- Inspect every linked evaluation's source locator before citing a result.; Compare predicted DE proportions with the printed true DE prevalence, not with each other alone.
- limitations
- Preprint; one 60/40 perturbation split per cell line; no spread printed.; The printed tables are DE-call proportions and accuracy by effect-size quantile; the macro-F1 and balanced accuracy comparisons are in figures only.; Majority-vote accuracy is near 100% in low-effect quantiles because almost all pairs are non-DE; read the Q5 column and the DE proportions together.; Which data setting (full or PerturbQA-downsampled) the tables report is not printed (source evidence concern).; The authors built the majority-vote, KNN, logistic-regression and scGen-based VAE comparators, and co-author Ouyang Zhu developed Scouter (reference 14); those rows are author-reported. scVI is run through STATE's benchmarking implementation with GenePT perturbation embeddings.; Ground-truth DE labels are Wilcoxon calls (BH-adjusted p < 0.01) on observed expression in four essential-gene Perturb-seq screens, not orthogonally validated effects.
- citation locators
- source id: lit-cells-networks-20261011-sun2026de-source-sun2026; locator: Tables 1-2; Sections 2.1 and 3.1-3.3
- source locator
- lit-cells-networks-20261011-sun2026de-source-sun2026: Tables 1-2; Sections 2.1 and 3.1-3.3
- headline metric
- accuracy
- comparison group
- sun2026-de-classification
- comparison title
- DE classification benchmark (Sun et al. 2026)
- stratum label
- Unseen perturbations within a cell line
- stratum order
- 1
- reviewed evaluations
- lit-cells-networks-20261011-sun2026de-eval-within-average-1-nn; lit-cells-networks-20261011-sun2026de-eval-within-average-10-nn; lit-cells-networks-20261011-sun2026de-eval-within-average-logistic-regression; lit-cells-networks-20261011-sun2026de-eval-within-average-majority-vote; lit-cells-networks-20261011-sun2026de-eval-within-average-scouter; lit-cells-networks-20261011-sun2026de-eval-within-average-scvi-mean; lit-cells-networks-20261011-sun2026de-eval-within-average-scvi-sampling; lit-cells-networks-20261011-sun2026de-eval-within-average-vae-scgen; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-1-nn; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-10-nn; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-logistic-regression; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-majority-vote; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-scouter; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-scvi-mean; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-scvi-sampling; lit-cells-networks-20261011-sun2026de-eval-within-hepg2-vae-scgen; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-1-nn; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-10-nn; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-logistic-regression; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-majority-vote; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-scouter; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-scvi-mean; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-scvi-sampling; lit-cells-networks-20261011-sun2026de-eval-within-jurkat-vae-scgen; lit-cells-networks-20261011-sun2026de-eval-within-k562-1-nn; lit-cells-networks-20261011-sun2026de-eval-within-k562-10-nn; lit-cells-networks-20261011-sun2026de-eval-within-k562-logistic-regression; lit-cells-networks-20261011-sun2026de-eval-within-k562-majority-vote; lit-cells-networks-20261011-sun2026de-eval-within-k562-scouter; lit-cells-networks-20261011-sun2026de-eval-within-k562-scvi-mean; lit-cells-networks-20261011-sun2026de-eval-within-k562-scvi-sampling; lit-cells-networks-20261011-sun2026de-eval-within-k562-vae-scgen; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-1-nn; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-10-nn; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-logistic-regression; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-majority-vote; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-scouter; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-scvi-mean; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-scvi-sampling; lit-cells-networks-20261011-sun2026de-eval-within-rpe1-vae-scgen
- reason
- Add a relevance judgement for a protocol from the 2026-10-11 cells-spatial and networks-mechanistic literature pass, reviewed in docs/reviews/2026-10-12-cells-networks-batches.md.
- review
- method: ai-assisted-source-review; scope-review; method note: Reviewer checked the endpoint against the use case's inputs, output and exclusions, the relevance rating and the limitations; every evaluation on the protocol had its values checked in the batch review. Corrections listed in review.md were applied by the extractor.; reviewer: claude; reviewer note: Claude review agent reviewer-cn-1, independent of the extractor lit-cells-networks; no human review claimed; reviewed at: 2026-10-12T08:40:00Z; note: Automated review; not human scientific review.
- pins
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