Configuration

scGPT_zero (SCMBench)

Evidence concern: excluded from comparisons

Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H

'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows

In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20

scGPT_zero: scGPT zero-shot embeddings per omic; Defaults for R methods and methods without explicit hyperparameters; tuned otherwise.

6 evaluations · 6 results 4 open disagreements between studies involve its model

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Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

6 evaluations · 6 results. Different protocols are not a single leaderboard.

Protocol: SCMBench unpaired RNA-ATAC integration accuracy

Sorted by Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Protocol and dataset	Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI)	Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI; mean across the five Muto-2021 batches (Yao not scored))
scGPT_zero (SCMBench)Evaluation	Muto-2021-batch-2 (SCMBench)	0.57 (best in column)	Not reported
scGPT_zero (SCMBench)Evaluation	Muto-2021-batch-3 (SCMBench)	0.545	Not reported
scGPT_zero (SCMBench)Evaluation	Muto-2021-batch-1 (SCMBench)	0.534	Not reported
scGPT_zero (SCMBench)Evaluation	Muto-2021-batch-4 (SCMBench)	0.527	Not reported
scGPT_zero (SCMBench)Evaluation	Muto-2021-batch-5 (SCMBench)	0.502	Not reported
scGPT_zero (SCMBench)Evaluation	unpaired-overall (SCMBench)	Not reported	0.536

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-1 (SCMBench)	0.534 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-1 lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell C10 (row 'scGPT_zero', column 'Muto-2021-batch-1')
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-2 (SCMBench)	0.57 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-2 lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell D10 (row 'scGPT_zero', column 'Muto-2021-batch-2')
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-3 (SCMBench)	0.545 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-3 lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell E10 (row 'scGPT_zero', column 'Muto-2021-batch-3')
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-4 (SCMBench)	0.527 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-4 lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell F10 (row 'scGPT_zero', column 'Muto-2021-batch-4')
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-5 (SCMBench)	0.502 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-5 lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell G10 (row 'scGPT_zero', column 'Muto-2021-batch-5')
Configuration: scGPT_zero (SCMBench)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: unpaired-overall (SCMBench)	0.536 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI; mean across the five Muto-2021 batches (Yao not scored)) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Evidence concern: excluded from comparisons Sheet 'unpaired_inte_overall' has no header for column H. Each H cell is the formula =AVERAGE(Bn:Gn), the mean of the dataset cells with values. Rows with a blank Yao cell (bindSC, scMoMaT, scGPT_zero, Pamona, scFoundation, Geneformer) average five datasets and the other rows six, so column H values are not comparable across all rows.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', row 1 and column H 'FM-scVI' is a different foundation model per dataset ('the best-performing foundation model combined with scVI, which varies across datasets', Fig. 2 legend), so its rows do not describe one fixed configuration.SCMBench Supplementary Data 2 (integration results) · Article Fig. 2 legend; Supplementary Data 2 'FM-scVI' rows In sheet 'paired_inte_overall' the scGPT row is scored on 10x-Multiome-Pbmc10k only; its Overall cell G20 (=AVERAGE(B20:F20)) is that single value, not a five-dataset mean, so it is not comparable with the other Overall values.SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'paired_inte_overall', cell G20 Methods, coverage and source scGPT_zero on SCMBench unpaired integration, unpaired-overall lit-cells-networks-20261011-scmbench-protocol-unpaired-integration-accuracy Aggregation: Not reported SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration; SCMBench Supplementary Data 2 (integration results) · Supplementary Data 2, sheet 'unpaired_inte_overall', cell H10 (row 'scGPT_zero', column 'unlabelled column H')

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SCMBench: benchmarking domain-specific and foundation models for single-cell multi-omics data integration · Original source · Published article, Nature Communications 2026 (PMC13342640.1)
SCMBench Supplementary Data 2 (integration results) · Original source · Supplementary Data 2 (MOESM4) of the published article

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Stable ID: lit-cells-networks-20261011-scmbench-config-scgpt-zero

areas: single-cell
contexts: research
method types: foundation_model
reported name: scGPT_zero
foundation model eligible: true
hyperparameters: Defaults for R methods and methods without explicit hyperparameters; tuned otherwise (Methods 'Hyperparameter tuning')
source locator: Supplementary Data 2 method rows; Methods 'Benchmarking setup'
missing metadata: version: reason: unreported
provenance note: scGPT_zero as run in SCMBench: scGPT zero-shot embeddings per omic.

Related records

configuration of: scGPT
system: scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-1
system: scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-2
system: scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-3
system: scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-4
system: scGPT_zero on SCMBench unpaired integration, Muto-2021-batch-5
system: scGPT_zero on SCMBench unpaired integration, unpaired-overall

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