Contested result

MutFormer and VEST4: Livesey and Marsh 2025, Genome Biology 26:104 (Europe PMC full text XML) and An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers disagree

Low severity
Not yet reviewed
two-study-conflict
unknown

Livesey and Marsh 2025, Genome Biology 26:104 (Europe PMC full text XML) ranks MutFormer above VEST4 in 6 of 7 comparisons; An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers ranks VEST4 above MutFormer in 6 of 6 comparisons. No other study gives a verdict, so neither is the outlier.

An automatic lead, not a finding of error. The results below are shown as published, everywhere on the site, until a reviewer decides otherwise.

Which studies agree

2 papers rank MutFormer above VEST4 in 6 of their 13 comparisons and VEST4 higher in 7. Of those papers, An openly licensed benchmark… ranks VEST4 higher on its own (6 of 6).

Rank MutFormer higher (1): Livesey and Marsh 2025
Rank VEST4 higher (1): An openly licensed benchmark…
Mixed (0): none

Each paper sits where at least two thirds of its comparisons point; Mixed means neither model reaches two thirds. The larger, outlined dot is the paper that disagrees.

MutFormer higherTieVEST4 higherNumbers are counts of comparisons; the outlined bar is the paper that disagrees.

Papers compared (2)
Paper	Role	Ranks MutFormer higher	Ranks VEST4 higher	Ties
Livesey and Marsh 2025, Genome Biology 26:104 (Europe PMC full text XML) and 1 more record · DOI	Agrees	6	1	0
An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers and 1 more record · DOI	Agrees	0	6	0

Comparisons in Livesey and Marsh 2025 (7)

Protocol	Dataset	Metric	MutFormer	VEST4	Higher
Livesey and Marsh 2025 clinical benchmark: pairwise AUROC win rate, ClinVar pathogenic versus gnomAD missense	Livesey and Marsh 2025 clinical set: ClinVar pathogenic versus gnomAD v4.1 missense (819 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, per-protein AUROC on shared variants, ClinVar P/LP versus gnomAD v4.1 missense, proteins with at least 10 of each), percent	64	77.1	VEST4
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, all 36 DMS sets	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, \|Spearman\| with DMS on shared variants, 36 human DMS sets), percent	71.4	59	MutFormer
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, all 36 DMS sets	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against the five top-ranked VEPs (column top_5_winrate; the five are not listed in the table), \|Spearman\| with DMS on shared variants, 36 human DMS sets), percent	17.2	2.33	MutFormer
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, direct assays only	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, \|Spearman\| with DMS on shared variants, direct DMS assays only), percent	74.7	59.9	MutFormer
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, indirect assays only	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, \|Spearman\| with DMS on shared variants, indirect DMS assays only), percent	68.9	58.4	MutFormer
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, SNV-accessible substitutions only	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, \|Spearman\| with DMS on shared variants, SNV-accessible substitutions only), percent	71.4	59	MutFormer
Livesey and Marsh 2025 DMS benchmark: pairwise \|Spearman\| win rate, SNV-accessible substitutions with gaps filled	Livesey and Marsh 2025 human DMS benchmark set (36 proteins)	Pairwise win rate (average pairwise win rate against all other VEPs, \|Spearman\| with DMS, SNV-accessible substitutions, missing predictions filled with the VEP's most benign score), percent	70.5	60.5	MutFormer

Comparisons in An openly licensed benchmark… (6)

Protocol	Dataset	Metric	MutFormer	VEST4	Higher
CGC missense oncogenicity, all genes (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	AUROC (CGC missense, all genes), unitless	0.693	0.833	VEST4
CGC missense oncogenicity, all genes (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	Average precision (CGC missense, all genes), unitless	0.446	0.648	VEST4
CGC missense oncogenicity, oncogenes (gain of function) (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	AUROC (CGC missense, oncogenes (gain of function)), unitless	0.768	0.84	VEST4
CGC missense oncogenicity, oncogenes (gain of function) (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	Average precision (CGC missense, oncogenes (gain of function)), unitless	0.582	0.713	VEST4
CGC missense oncogenicity, tumour suppressors (loss of function) (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	AUROC (CGC missense, tumour suppressors (loss of function)), unitless	0.655	0.885	VEST4
CGC missense oncogenicity, tumour suppressors (loss of function) (Lee 2026, OncoCal tool_performance.tsv)	Missense variants in 768 Cancer Gene Census genes with open oncogenicity labels	Average precision (CGC missense, tumour suppressors (loss of function)), unitless	0.286	0.626	VEST4

What disagrees

studies: 2

Compared: MutFormer, VEST4
Study that disagrees
Other studies
Rule: two-study-conflict; unknown
Model identity: Matched across studies partly through links not yet reviewed

Follow-up

Current state: Not yet reviewed.

No one has reviewed this finding yet.

How to help resolve this

If you know why these studies disagree, for example a different population, metric or preprocessing step, or you have a corrected value, tell us through the contribution form. A reviewer checks every submission against its source before anything changes, and the step is added to the follow-up above.

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