Configuration

FM-scVI (SCMBench adapter)

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

FM-scVI, a configuration of scGPT and UCE (Universal Cell Embeddings): SCMBench authors' adapter: embeddings from a foundation model fed to scVI; the foundation model is the best one per dataset; Foundation model embeddings with an scVI integration module.

13 evaluations · 13 results

Overview

An explanatory profile has not yet been reviewed for this record.

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

Evaluations and results

13 evaluations · 13 results. Different protocols are not a single leaderboard.

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 datasets)
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, 10x-Multiome-Pbmc10k (SCMBench)	0.674 (best in column)	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Muto-2021-batch-3 (SCMBench)	0.603	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Muto-2021-batch-2 (SCMBench)	0.599	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Muto-2021-batch-4 (SCMBench)	0.58	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Muto-2021-batch-1 (SCMBench)	0.576	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, Chen-2019 (SCMBench)	0.568	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Muto-2021-batch-5 (SCMBench)	0.55	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, Yao (SCMBench)	0.51	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, Ma-2020-batch-55 (SCMBench)	0.3	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, Ma-2020-batch-54 (SCMBench)	0.295	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, Ma-2020-batch-53 (SCMBench)	0.278	Not reported
FM-scVI (SCMBench adapter)Evaluation	SCMBench paired RNA-ATAC integration accuracy, paired-overall (SCMBench)	Not reported	0.423
FM-scVI (SCMBench adapter)Evaluation	SCMBench unpaired RNA-ATAC integration accuracy, unpaired-overall (SCMBench)	Not reported	0.57 (best in column)

All 13 result rows with coverage, uncertainty and sources

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: 10x-Multiome-Pbmc10k (SCMBench)	0.674 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	Author-reported 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 FM-scVI on SCMBench paired integration, 10x-Multiome-Pbmc10k lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell B23 (row 'FM-scVI', column '10x-Multiome-Pbmc10k')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: Chen-2019 (SCMBench)	0.568 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	Author-reported 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 FM-scVI on SCMBench paired integration, Chen-2019 lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell C23 (row 'FM-scVI', column 'Chen-2019')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: Ma-2020-batch-53 (SCMBench)	0.278 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	Author-reported 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 FM-scVI on SCMBench paired integration, Ma-2020-batch-53 lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell D23 (row 'FM-scVI', column 'Ma-2020-batch-53')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: Ma-2020-batch-54 (SCMBench)	0.295 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	Author-reported 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 FM-scVI on SCMBench paired integration, Ma-2020-batch-54 lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell E23 (row 'FM-scVI', column 'Ma-2020-batch-54')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: Ma-2020-batch-55 (SCMBench)	0.3 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	Author-reported 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 FM-scVI on SCMBench paired integration, Ma-2020-batch-55 lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell F23 (row 'FM-scVI', column 'Ma-2020-batch-55')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench paired RNA-ATAC integration accuracy Dataset subset: paired-overall (SCMBench)	0.423 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI; mean across datasets) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported 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 FM-scVI on SCMBench paired integration, paired-overall lit-cells-networks-20261011-scmbench-protocol-paired-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 'paired_inte_overall', cell G23 (row 'FM-scVI', column 'Overall')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-1 (SCMBench)	0.576 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	Author-reported 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 FM-scVI 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 C18 (row 'FM-scVI', column 'Muto-2021-batch-1')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-2 (SCMBench)	0.599 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	Author-reported 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 FM-scVI 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 D18 (row 'FM-scVI', column 'Muto-2021-batch-2')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-3 (SCMBench)	0.603 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	Author-reported 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 FM-scVI 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 E18 (row 'FM-scVI', column 'Muto-2021-batch-3')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-4 (SCMBench)	0.58 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	Author-reported 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 FM-scVI 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 F18 (row 'FM-scVI', column 'Muto-2021-batch-4')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Muto-2021-batch-5 (SCMBench)	0.55 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	Author-reported 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 FM-scVI 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 G18 (row 'FM-scVI', column 'Muto-2021-batch-5')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: unpaired-overall (SCMBench)	0.57 Scmbench integration accuracy (mean of MAP, NMI, ASW and ARI; mean across datasets) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported 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 FM-scVI 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 H18 (row 'FM-scVI', column 'unlabelled column H')
Configuration: FM-scVI (SCMBench adapter)	Protocol: SCMBench unpaired RNA-ATAC integration accuracy Dataset subset: Yao (SCMBench)	0.51 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	Author-reported 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 FM-scVI on SCMBench unpaired integration, Yao 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 B18 (row 'FM-scVI', column 'Yao')

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Release 2026-10-23-5347695500ed · Record review: source checked

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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-fm-scvi

areas: single-cell
contexts: research
method types: foundation_model
reported name: FM-scVI
foundation model eligible: true
training setting: Foundation model embeddings with an scVI integration module
source locator: Fig. 2 legend; Results on FM adaptation
limitations: The underlying foundation model differs by dataset.
missing metadata: version: reason: unreported
provenance note: SCMBench authors' adapter: embeddings from a foundation model fed to scVI; the foundation model is the best one per dataset (scGPT on PBMC-10k, adapted UCE on Ma-2020, per the Fig. 2 legend).

Related records

uses model: scGPT
uses model: UCE (Universal Cell Embeddings)
system: FM-scVI on SCMBench paired integration, 10x-Multiome-Pbmc10k
system: FM-scVI on SCMBench paired integration, Chen-2019
system: FM-scVI on SCMBench paired integration, Ma-2020-batch-53
system: FM-scVI on SCMBench paired integration, Ma-2020-batch-54
system: FM-scVI on SCMBench paired integration, Ma-2020-batch-55
system: FM-scVI on SCMBench paired integration, paired-overall
system: FM-scVI on SCMBench unpaired integration, Muto-2021-batch-1
system: FM-scVI on SCMBench unpaired integration, Muto-2021-batch-2
system: FM-scVI on SCMBench unpaired integration, Muto-2021-batch-3
system: FM-scVI on SCMBench unpaired integration, Muto-2021-batch-4
system: FM-scVI on SCMBench unpaired integration, Muto-2021-batch-5
system: FM-scVI on SCMBench unpaired integration, unpaired-overall
system: FM-scVI on SCMBench unpaired integration, Yao

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