Protocol

Allelic reporter effect correlation in K562 (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.

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

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

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 K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.033 pearson-correlation unitless · higher Uncertainty: SE 0.016. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Borzoi', column 'K562 (19,321 SNPs)'
Configuration: Caduceus (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.133 pearson-correlation unitless · higher Uncertainty: SE 0.030. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Caduceus', column 'K562 (19,321 SNPs)'
Configuration: ChromBPNet (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.287 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 ChromBPNet on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'ChromBPNet', column 'K562 (19,321 SNPs)'
Configuration: DNABERT-2 (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.086 pearson-correlation unitless · higher Uncertainty: SE 0.039. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'DNABERT-2', column 'K562 (19,321 SNPs)'
Configuration: Enformer (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.059 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 Enformer on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Enformer', column 'K562 (19,321 SNPs)'
Configuration: Gena LM b-multi (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.077 pearson-correlation unitless · higher Uncertainty: SE 0.051. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM b-multi', column 'K562 (19,321 SNPs)'
Configuration: Gena LM-base (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.077 pearson-correlation unitless · higher Uncertainty: SE 0.042. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM-base', column 'K562 (19,321 SNPs)'
Configuration: Gena LM bigbird (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.136 pearson-correlation unitless · higher Uncertainty: SE 0.055. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM bigbird', column 'K562 (19,321 SNPs)'
Configuration: Gena LM large (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.117 pearson-correlation unitless · higher Uncertainty: SE 0.044. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Gena LM large', column 'K562 (19,321 SNPs)'
Configuration: Geneformer (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.005 pearson-correlation unitless · higher Uncertainty: SE 0.198. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Geneformer', column 'K562 (19,321 SNPs)'
Configuration: Hyenadna 1 mf (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.118 pearson-correlation unitless · higher Uncertainty: SE 0.056. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 1 mf', column 'K562 (19,321 SNPs)'
Configuration: Hyenadna 160 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.148 pearson-correlation unitless · higher Uncertainty: SE 0.053. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 160 k', column 'K562 (19,321 SNPs)'
Configuration: Hyenadna 32 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.084 pearson-correlation unitless · higher Uncertainty: SE 0.071. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 32 k', column 'K562 (19,321 SNPs)'
Configuration: Hyenadna 450 k (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.077 pearson-correlation unitless · higher Uncertainty: SE 0.074. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'Hyenadna 450 k', column 'K562 (19,321 SNPs)'
Configuration: NT 2.5b-1000g (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.147 pearson-correlation unitless · higher Uncertainty: SE 0.052. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-1000g', column 'K562 (19,321 SNPs)'
Configuration: NT 2.5b-m-s (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.153 pearson-correlation unitless · higher Uncertainty: SE 0.055. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 2.5b-m-s', column 'K562 (19,321 SNPs)'
Configuration: NT 500m-h-ref (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.149 pearson-correlation unitless · higher Uncertainty: SE 0.139. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m-h-ref', column 'K562 (19,321 SNPs)'
Configuration: NT 500m1000g (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.123 pearson-correlation unitless · higher Uncertainty: SE 0.084. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT 500m1000g', column 'K562 (19,321 SNPs)'
Configuration: NT v2-100m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.152 pearson-correlation unitless · higher Uncertainty: SE 0.065. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-100m-ms', column 'K562 (19,321 SNPs)'
Configuration: NT v2-250m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.166 pearson-correlation unitless · higher Uncertainty: SE 0.064. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-250m-ms', column 'K562 (19,321 SNPs)'
Configuration: NT v2 500m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.199 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 500m-ms on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2 500m-ms', column 'K562 (19,321 SNPs)'
Configuration: NT v2-50m-ms (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.147 pearson-correlation unitless · higher Uncertainty: SE 0.058. 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 K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'NT v2-50m-ms', column 'K562 (19,321 SNPs)'
Configuration: SEI (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.297 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 SEI on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'SEI', column 'K562 (19,321 SNPs)'
Configuration: TREDNet (Manzo et al. 2025)	Protocol: Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1) Dataset: K562 regulatory variant reporter data (Manzo et al. 2025)	0.315 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	Author-reported evaluation · Source checked Methods, coverage and source TREDNet on K562 reporter variant effects regulatory-variant-20261009-protocol-manzo2025-k562-pearson Aggregation: Not reported Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants · Table 1 row 'TREDNet', column 'K562 (19,321 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.

Explore all linked results

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

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

0 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-10-7fcc3e48a123
Property and statement	Original source and location	Review and provenance

No evidence rows match these filters. Choose another scope or clear the search.

All evidence (JSONL) (gzip)How to read the evidence

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

Download this release (gzip)

Technical metadata and extraction receipts

Stable ID: regulatory-variant-20261009-protocol-manzo2025-k562-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 'K562 (19,321 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.; K562 combines SuRE raQTLs (19,237) and an MPRA set (2,756), which sum to 21,993, not the 19,321 in the Table 1 header; no filtering step is stated.

Related records

uses data: K562 regulatory variant reporter data (Manzo et al. 2025)
subject: reported_summary: regulatory-variant-20261009-protocol-manzo2025-k562-pearson
subject: population_detail: regulatory-variant-20261009-protocol-manzo2025-k562-pearson
assessment: Borzoi on K562 reporter variant effects
assessment: Caduceus on K562 reporter variant effects
assessment: ChromBPNet on K562 reporter variant effects
assessment: DNABERT-2 on K562 reporter variant effects
assessment: Enformer on K562 reporter variant effects
assessment: Gena LM b-multi on K562 reporter variant effects
assessment: Gena LM-base on K562 reporter variant effects
assessment: Gena LM bigbird on K562 reporter variant effects
assessment: Gena LM large on K562 reporter variant effects
assessment: Geneformer on K562 reporter variant effects
assessment: Hyenadna 1 mf on K562 reporter variant effects
assessment: Hyenadna 160 k on K562 reporter variant effects
assessment: Hyenadna 32 k on K562 reporter variant effects
assessment: Hyenadna 450 k on K562 reporter variant effects
assessment: NT 2.5b-1000g on K562 reporter variant effects
assessment: NT 2.5b-m-s on K562 reporter variant effects
assessment: NT 500m-h-ref on K562 reporter variant effects
assessment: NT 500m1000g on K562 reporter variant effects
assessment: NT v2-100m-ms on K562 reporter variant effects
assessment: NT v2-250m-ms on K562 reporter variant effects
assessment: NT v2 500m-ms on K562 reporter variant effects
assessment: NT v2-50m-ms on K562 reporter variant effects
assessment: SEI on K562 reporter variant effects
assessment: TREDNet on K562 reporter variant effects
assessed by: Select regulatory variants and genes for functional follow-up

Suggest a correction