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Protocol

Allelic reporter effect correlation in HeLa (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.

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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 HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
−0.066 pearson-correlation
unitless · higher

Uncertainty: SE 0.005. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Borzoi', column 'Hela (5241 SNPs)'
Configuration: Caduceus (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.02 pearson-correlation
unitless · higher

Uncertainty: SE 0.022. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Caduceus', column 'Hela (5241 SNPs)'
Configuration: ChromBPNet (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.289 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

ChromBPNet on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'ChromBPNet', column 'Hela (5241 SNPs)'
Configuration: DNABERT-2 (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.12 pearson-correlation
unitless · higher

Uncertainty: SE 0.140. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'DNABERT-2', column 'Hela (5241 SNPs)'
Configuration: Enformer (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.245 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

Enformer on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Enformer', column 'Hela (5241 SNPs)'
Configuration: Gena LM b-multi (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.026 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

Gena LM b-multi on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM b-multi', column 'Hela (5241 SNPs)'
Configuration: Gena LM-base (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.029 pearson-correlation
unitless · higher

Uncertainty: SE 0.227. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM-base', column 'Hela (5241 SNPs)'
Configuration: Gena LM bigbird (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.045 pearson-correlation
unitless · higher

Uncertainty: SE 0.015. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM bigbird', column 'Hela (5241 SNPs)'
Configuration: Gena LM large (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.069 pearson-correlation
unitless · higher

Uncertainty: SE 0.216. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM large', column 'Hela (5241 SNPs)'
Configuration: Geneformer (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
−0.007 pearson-correlation
unitless · higher

Uncertainty: SE 0.057. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Geneformer', column 'Hela (5241 SNPs)'
Configuration: Hyenadna 1 mf (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.046 pearson-correlation
unitless · higher

Uncertainty: SE 0.013. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 1 mf', column 'Hela (5241 SNPs)'
Configuration: Hyenadna 160 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.046 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

Independent external evaluation · Source checked
Methods, coverage and source

Hyenadna 160 k on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 160 k', column 'Hela (5241 SNPs)'
Configuration: Hyenadna 32 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.031 pearson-correlation
unitless · higher

Uncertainty: SE 0.013. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 32 k', column 'Hela (5241 SNPs)'
Configuration: Hyenadna 450 k (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.055 pearson-correlation
unitless · higher

Uncertainty: SE 0.015. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 450 k', column 'Hela (5241 SNPs)'
Configuration: NT 2.5b-1000g (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.087 pearson-correlation
unitless · higher

Uncertainty: SE 0.105. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-1000g', column 'Hela (5241 SNPs)'
Configuration: NT 2.5b-m-s (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.066 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-m-s', column 'Hela (5241 SNPs)'
Configuration: NT 500m-h-ref (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.067 pearson-correlation
unitless · higher

Uncertainty: SE 0.043. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m-h-ref', column 'Hela (5241 SNPs)'
Configuration: NT 500m1000g (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.022 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

Independent external evaluation · Source checked
Methods, coverage and source

NT 500m1000g on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m1000g', column 'Hela (5241 SNPs)'
Configuration: NT v2-100m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.042 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 v2-100m-ms on HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-100m-ms', column 'Hela (5241 SNPs)'
Configuration: NT v2-250m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.03 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

Independent external evaluation · Source checked
Methods, coverage and source

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

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-250m-ms', column 'Hela (5241 SNPs)'
Configuration: NT v2 500m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.036 pearson-correlation
unitless · higher

Uncertainty: SE 0.011. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2 500m-ms', column 'Hela (5241 SNPs)'
Configuration: NT v2-50m-ms (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.074 pearson-correlation
unitless · higher

Uncertainty: SE 0.047. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-50m-ms', column 'Hela (5241 SNPs)'
Configuration: SEI (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.28 pearson-correlation
unitless · higher

Uncertainty: SE 0.008. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'SEI', column 'Hela (5241 SNPs)'
Configuration: TREDNet (Manzo et al. 2025)Protocol: Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)
Dataset: HeLa regulatory variant reporter data (Manzo et al. 2025)
0.076 pearson-correlation
unitless · higher

Uncertainty: SE 0.063. 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 HeLa reporter variant effects

regulatory-variant-20261009-protocol-manzo2025-hela-pearson

Aggregation: Not reported

Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'TREDNet', column 'Hela (5241 SNPs)'

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

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Author-reported evaluations
1
External evaluations
23

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Technical metadata and extraction receipts

Stable ID: regulatory-variant-20261009-protocol-manzo2025-hela-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 'Hela (5241 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.; HeLa is three coding-exon MPRA sets (SORL1, TRAF3IP2, PPARG; 5,241 SNPs in total).
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