Protocol

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

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

Overview

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

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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

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

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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: Borzoi (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.023 pearson-correlation unitless · higher Uncertainty: SE 0.004. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Borzoi', column 'NPC (14,042 SNPs)'
Configuration: Caduceus (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.023 pearson-correlation unitless · higher Uncertainty: SE 0.004. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Caduceus', column 'NPC (14,042 SNPs)'
Configuration: ChromBPNet (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.08 pearson-correlation unitless · higher Uncertainty: SE 0.001. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'ChromBPNet', column 'NPC (14,042 SNPs)'
Configuration: DNABERT-2 (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	−0.004 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 DNABERT-2 on NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'DNABERT-2', column 'NPC (14,042 SNPs)'
Configuration: Enformer (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.008 pearson-correlation unitless · higher Uncertainty: SE 0.080. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Enformer', column 'NPC (14,042 SNPs)'
Configuration: Gena LM b-multi (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.01 pearson-correlation unitless · higher Uncertainty: SE 0.001. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM b-multi', column 'NPC (14,042 SNPs)'
Configuration: Gena LM-base (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.024 pearson-correlation unitless · higher Uncertainty: SE 0.002. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM-base', column 'NPC (14,042 SNPs)'
Configuration: Gena LM bigbird (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.021 pearson-correlation unitless · higher Uncertainty: SE 0.002. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM bigbird', column 'NPC (14,042 SNPs)'
Configuration: Gena LM large (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.03 pearson-correlation unitless · higher Uncertainty: SE 0.002. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM large', column 'NPC (14,042 SNPs)'
Configuration: Geneformer (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	−0.002 pearson-correlation unitless · higher Uncertainty: SE 0.138. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Geneformer', column 'NPC (14,042 SNPs)'
Configuration: Hyenadna 1 mf (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.001 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 1 mf', column 'NPC (14,042 SNPs)'
Configuration: Hyenadna 160 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	−0.007 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 160 k', column 'NPC (14,042 SNPs)'
Configuration: Hyenadna 32 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.002 pearson-correlation unitless · higher Uncertainty: SE 0.002. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 32 k', column 'NPC (14,042 SNPs)'
Configuration: Hyenadna 450 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	−0.007 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 450 k', column 'NPC (14,042 SNPs)'
Configuration: NT 2.5b-1000g (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.005 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-1000g', column 'NPC (14,042 SNPs)'
Configuration: NT 2.5b-m-s (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.027 pearson-correlation unitless · higher Uncertainty: SE 0.001. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-m-s', column 'NPC (14,042 SNPs)'
Configuration: NT 500m-h-ref (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.013 pearson-correlation unitless · higher Uncertainty: SE 0.001. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m-h-ref', column 'NPC (14,042 SNPs)'
Configuration: NT 500m1000g (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.001 pearson-correlation unitless · higher Uncertainty: SE 0.002. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m1000g', column 'NPC (14,042 SNPs)'
Configuration: NT v2-100m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.016 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-100m-ms', column 'NPC (14,042 SNPs)'
Configuration: NT v2-250m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.023 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-250m-ms', column 'NPC (14,042 SNPs)'
Configuration: NT v2 500m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.028 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2 500m-ms', column 'NPC (14,042 SNPs)'
Configuration: NT v2-50m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.02 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-50m-ms', column 'NPC (14,042 SNPs)'
Configuration: SEI (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.073 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'SEI', column 'NPC (14,042 SNPs)'
Configuration: TREDNet (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1) Dataset: NPC regulatory variant reporter data (Manzo et al. 2025)	0.075 pearson-correlation unitless · higher Uncertainty: SE 0.003. 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 NPC reporter variant effects regulatory-variant-20261009-protocol-manzo2025-npc-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'TREDNet', column 'NPC (14,042 SNPs)'

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Author-reported evaluations: 1
External evaluations: 23

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Sources and history

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Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Original source · Genes 16(10):1223, published 2025-10-15; PMC12562713 full-text XML

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Technical metadata and extraction receipts

Stable ID: regulatory-variant-20261009-protocol-manzo2025-npc-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 'NPC (14,042 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.; NPC is one lentiMPRA set of 14,042 variants fixed in modern humans, tested in neural progenitor cells.

Related records

uses data: NPC regulatory variant reporter data (Manzo et al. 2025)
assessment: Borzoi on NPC reporter variant effects
assessment: Caduceus on NPC reporter variant effects
assessment: ChromBPNet on NPC reporter variant effects
assessment: DNABERT-2 on NPC reporter variant effects
assessment: Enformer on NPC reporter variant effects
assessment: Gena LM b-multi on NPC reporter variant effects
assessment: Gena LM-base on NPC reporter variant effects
assessment: Gena LM bigbird on NPC reporter variant effects
assessment: Gena LM large on NPC reporter variant effects
assessment: Geneformer on NPC reporter variant effects
assessment: Hyenadna 1 mf on NPC reporter variant effects
assessment: Hyenadna 160 k on NPC reporter variant effects
assessment: Hyenadna 32 k on NPC reporter variant effects
assessment: Hyenadna 450 k on NPC reporter variant effects
assessment: NT 2.5b-1000g on NPC reporter variant effects
assessment: NT 2.5b-m-s on NPC reporter variant effects
assessment: NT 500m-h-ref on NPC reporter variant effects
assessment: NT 500m1000g on NPC reporter variant effects
assessment: NT v2-100m-ms on NPC reporter variant effects
assessment: NT v2-250m-ms on NPC reporter variant effects
assessment: NT v2 500m-ms on NPC reporter variant effects
assessment: NT v2-50m-ms on NPC reporter variant effects
assessment: SEI on NPC reporter variant effects
assessment: TREDNet on NPC reporter variant effects
assessed by: Select regulatory variants and genes for functional follow-up

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