rewirebio.iobenchmarks
Protocol

Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)

Pearson correlation between predicted and measured log2 fold-change of variant effects in reporter assays.

24 evaluations · 24 results

Overview

Pearson correlation between predicted and measured log2 fold-change of variant effects in reporter assays.

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

24 recorded evaluations, 24 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.

View coverage and remaining gaps across all benchmarks

Results

Results are available, but no reviewed comparison panel is linked in this release.

All evaluations

24 evaluations · 24 results. Different protocols are not a single leaderboard.

Filter evaluations

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configurationProtocol and datasetFindingEvidence and details
Configuration: Borzoi (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.125 pearson-correlation
unitless · higher

Uncertainty: SE 0.025. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Borzoi on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Borzoi', column 'HepG2 (16,255 SNPs)'
Configuration: Caduceus (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.108 pearson-correlation
unitless · higher

Uncertainty: SE 0.021. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Caduceus on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Caduceus', column 'HepG2 (16,255 SNPs)'
Configuration: ChromBPNet (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.295 pearson-correlation
unitless · higher

Uncertainty: SE 0.021. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

ChromBPNet on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'ChromBPNet', column 'HepG2 (16,255 SNPs)'
Configuration: DNABERT-2 (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.096 pearson-correlation
unitless · higher

Uncertainty: SE 0.191. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

DNABERT-2 on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'DNABERT-2', column 'HepG2 (16,255 SNPs)'
Configuration: Enformer (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.141 pearson-correlation
unitless · higher

Uncertainty: SE 0.110. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Enformer on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Enformer', column 'HepG2 (16,255 SNPs)'
Configuration: Gena LM b-multi (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.062 pearson-correlation
unitless · higher

Uncertainty: SE 0.024. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Gena LM b-multi on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM b-multi', column 'HepG2 (16,255 SNPs)'
Configuration: Gena LM-base (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.05 pearson-correlation
unitless · higher

Uncertainty: SE 0.033. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Gena LM-base on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM-base', column 'HepG2 (16,255 SNPs)'
Configuration: Gena LM bigbird (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.099 pearson-correlation
unitless · higher

Uncertainty: SE 0.029. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Gena LM bigbird on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM bigbird', column 'HepG2 (16,255 SNPs)'
Configuration: Gena LM large (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.088 pearson-correlation
unitless · higher

Uncertainty: SE 0.036. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Gena LM large on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM large', column 'HepG2 (16,255 SNPs)'
Configuration: Geneformer (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.027 pearson-correlation
unitless · higher

Uncertainty: SE 0.160. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Geneformer on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Geneformer', column 'HepG2 (16,255 SNPs)'
Configuration: Hyenadna 1 mf (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.136 pearson-correlation
unitless · higher

Uncertainty: SE 0.059. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Hyenadna 1 mf on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 1 mf', column 'HepG2 (16,255 SNPs)'
Configuration: Hyenadna 160 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.142 pearson-correlation
unitless · higher

Uncertainty: SE 0.040. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Hyenadna 160 k on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 160 k', column 'HepG2 (16,255 SNPs)'
Configuration: Hyenadna 32 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.098 pearson-correlation
unitless · higher

Uncertainty: SE 0.061. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Hyenadna 32 k on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 32 k', column 'HepG2 (16,255 SNPs)'
Configuration: Hyenadna 450 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.134 pearson-correlation
unitless · higher

Uncertainty: SE 0.050. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

Hyenadna 450 k on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 450 k', column 'HepG2 (16,255 SNPs)'
Configuration: NT 2.5b-1000g (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.112 pearson-correlation
unitless · higher

Uncertainty: SE 0.021. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT 2.5b-1000g on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-1000g', column 'HepG2 (16,255 SNPs)'
Configuration: NT 2.5b-m-s (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.139 pearson-correlation
unitless · higher

Uncertainty: SE 0.027. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT 2.5b-m-s on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-m-s', column 'HepG2 (16,255 SNPs)'
Configuration: NT 500m-h-ref (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.119 pearson-correlation
unitless · higher

Uncertainty: SE 0.038. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT 500m-h-ref on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m-h-ref', column 'HepG2 (16,255 SNPs)'
Configuration: NT 500m1000g (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.116 pearson-correlation
unitless · higher

Uncertainty: SE 0.023. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT 500m1000g on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m1000g', column 'HepG2 (16,255 SNPs)'
Configuration: NT v2-100m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.127 pearson-correlation
unitless · higher

Uncertainty: SE 0.050. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT v2-100m-ms on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-100m-ms', column 'HepG2 (16,255 SNPs)'
Configuration: NT v2-250m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.11 pearson-correlation
unitless · higher

Uncertainty: SE 0.020. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT v2-250m-ms on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-250m-ms', column 'HepG2 (16,255 SNPs)'
Configuration: NT v2 500m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.114 pearson-correlation
unitless · higher

Uncertainty: SE 0.007. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT v2 500m-ms on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2 500m-ms', column 'HepG2 (16,255 SNPs)'
Configuration: NT v2-50m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.103 pearson-correlation
unitless · higher

Uncertainty: SE 0.036. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

NT v2-50m-ms on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-50m-ms', column 'HepG2 (16,255 SNPs)'
Configuration: SEI (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.298 pearson-correlation
unitless · higher

Uncertainty: SE 0.029. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Independent external evaluation · Source checked
Methods, coverage and source

SEI on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'SEI', column 'HepG2 (16,255 SNPs)'
Configuration: TREDNet (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)
Dataset: HepG2 regulatory variant reporter data (Manzo et al. 2025)
0.314 pearson-correlation
unitless · higher

Uncertainty: SE 0.018. Standard error as printed in brackets; its basis is not defined in the caption

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

TREDNet on HepG2 reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'TREDNet', column 'HepG2 (16,255 SNPs)'

Source checking is not independent reproduction. Release 2026-10-10-7fcc3e48a123.

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1
External evaluations
23

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Technical metadata and extraction receipts

Stable ID: regulatory-variant-20261009-protocol-manzo2025-hepg2-pearson

areas
dna-genomes
contexts
research
protocol
Score 1 kb reference and alternative sequences centred on each SNP; correlate the predicted log2 ratio with the experimental log2 fold-change; standard error in brackets.
version
Table 1
source locator
Table 1 column 'HepG2 (16,255 SNPs)'; Results 2.1; Methods 4.1
limitations
Reporter (SuRE, MPRA, luciferase) activity on episomal constructs, not endogenous regulation.; TREDNet was developed by the senior author's group (reference 18) and is author_reported; the other 23 models were run by the authors.; Models were not adapted equally: Transformers were fine-tuned for enhancer classification per cell line; CNNs and long-context models were used for inference. The source describes the adaptation of Enformer, Borzoi and HyenaDNA inconsistently (Table 2 versus Section 4.2); Enformer and Borzoi are excluded from this judgement for that reason.; Geneformer, a single-cell transcriptome model, was applied to DNA tokens; it is excluded from this judgement.; The bracketed values are labelled standard errors; how they were computed is not stated.; Results 2.1 and 2.3 give dataset-averaged values that differ from Table 1, and the HeLa ranking in the text differs from the table; table values are recorded.; HepG2 combines SuRE raQTLs (14,183), a SORT1 luciferase saturation set and 284 MPRA SNPs; the 16,255 header count is not explained.
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