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.
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.
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
| Tested configuration | Protocol and dataset | Finding | Evidence 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 checkedMethods, coverage and sourceBorzoi 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 checkedMethods, coverage and sourceCaduceus 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 checkedMethods, coverage and sourceChromBPNet 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 checkedMethods, coverage and sourceDNABERT-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 checkedMethods, coverage and sourceEnformer 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 checkedMethods, coverage and sourceGena 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 checkedMethods, coverage and sourceGena 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 checkedMethods, coverage and sourceGena 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 checkedMethods, coverage and sourceGena 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 checkedMethods, coverage and sourceGeneformer 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 checkedMethods, coverage and sourceHyenadna 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 checkedMethods, coverage and sourceHyenadna 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 checkedMethods, coverage and sourceHyenadna 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 checkedMethods, coverage and sourceHyenadna 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceNT 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 checkedMethods, coverage and sourceSEI 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 checkedMethods, coverage and sourceTREDNet 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.
Methods and evaluation design
Procedure, tasks and evaluated configurations
Recorded evaluations
Each evaluation records what was tested and under which conditions.
- Borzoi on HepG2 reporter variant effects
- Caduceus on HepG2 reporter variant effects
- ChromBPNet on HepG2 reporter variant effects
- DNABERT-2 on HepG2 reporter variant effects
- Enformer on HepG2 reporter variant effects
- Gena LM b-multi on HepG2 reporter variant effects
- Gena LM-base on HepG2 reporter variant effects
- Gena LM bigbird on HepG2 reporter variant effects
- Gena LM large on HepG2 reporter variant effects
- Geneformer on HepG2 reporter variant effects
- Hyenadna 1 mf on HepG2 reporter variant effects
- Hyenadna 160 k on HepG2 reporter variant effects
Baseline coverage
Reference methods help show what a model adds beyond simple controls. We track a null control and a conventional method for each protocol.
0 of 2 active baseline roles have published Rewire measurements in this release. Measurements on a selected protocol do not establish coverage of an entire suite.
No execution recipe linked to this protocol. Recipe availability does not establish a completed evaluation.
- Author-reported evaluations
- 1
- External evaluations
- 23
Literature evidence is not a Rewire measurement. Executed but unpublished runs and private review status are not included.
Null control
Proposed control: requires review
Select a task-valid null control after reviewing inputs and metric
Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.
This is a suggested selection rule, not a validated method or a measured score.
Conventional reference
Proposed control: requires review
Select an upstream conventional reference after reviewing the full protocol
Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.
This is a suggested selection rule, not a validated method or a measured score.
Protocol coverage CSV (gzip) · Model evaluation matrix (gzip) · Source table (gzip) · Release and checksums (gzip)
Coverage is derived from release 2026-10-10-7fcc3e48a123. Source citations describe the original records; they do not validate an unreviewed baseline proposal. No results have been generated by this audit.
Run instructions
No runnable recipe has been reviewed for this protocol. Dataset access, model requirements, licences and compute requirements must be checked against its sources before execution.
Strengths, limitations and unresolved questions
Evidence
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Evidence table
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Sources and history
Release 2026-10-10-7fcc3e48a123 · Record review: source checked
1 source records and release history
- 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
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.
Related records
- uses data: HepG2 regulatory variant reporter data (Manzo et al. 2025)
- assessment: Borzoi on HepG2 reporter variant effects
- assessment: Caduceus on HepG2 reporter variant effects
- assessment: ChromBPNet on HepG2 reporter variant effects
- assessment: DNABERT-2 on HepG2 reporter variant effects
- assessment: Enformer on HepG2 reporter variant effects
- assessment: Gena LM b-multi on HepG2 reporter variant effects
- assessment: Gena LM-base on HepG2 reporter variant effects
- assessment: Gena LM bigbird on HepG2 reporter variant effects
- assessment: Gena LM large on HepG2 reporter variant effects
- assessment: Geneformer on HepG2 reporter variant effects
- assessment: Hyenadna 1 mf on HepG2 reporter variant effects
- assessment: Hyenadna 160 k on HepG2 reporter variant effects
- assessment: Hyenadna 32 k on HepG2 reporter variant effects
- assessment: Hyenadna 450 k on HepG2 reporter variant effects
- assessment: NT 2.5b-1000g on HepG2 reporter variant effects
- assessment: NT 2.5b-m-s on HepG2 reporter variant effects
- assessment: NT 500m-h-ref on HepG2 reporter variant effects
- assessment: NT 500m1000g on HepG2 reporter variant effects
- assessment: NT v2-100m-ms on HepG2 reporter variant effects
- assessment: NT v2-250m-ms on HepG2 reporter variant effects
- assessment: NT v2 500m-ms on HepG2 reporter variant effects
- assessment: NT v2-50m-ms on HepG2 reporter variant effects
- assessment: SEI on HepG2 reporter variant effects
- assessment: TREDNet on HepG2 reporter variant effects
- assessed by: Select regulatory variants and genes for functional follow-up