PHACTboost and BayesDel: An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers reverses the order
- Low severity
- Not yet reviewed
- Ordering reversal
- Different tasks across studies
An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers ranks BayesDel above PHACTboost in 4 of 5 comparisons; other studies rank PHACTboost above BayesDel in 7 of 7.
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
Livesey and Marsh 2025 ranks PHACTboost above BayesDel in all 7 of its comparisons. An openly licensed benchmark… ranks BayesDel above PHACTboost in 4 of its 6 comparisons and PHACTboost higher in 1; 1 is a tie.
- Rank PHACTboost higher (1): Livesey and Marsh 2025
- Rank BayesDel higher (1): An openly licensed benchmark… (disagrees)
- 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.
| Paper | Role | Ranks PHACTboost higher | Ranks BayesDel higher | Ties |
|---|---|---|---|---|
| An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers and 1 more record · DOI | Disagrees | 1 | 4 | 1 |
| Livesey and Marsh 2025, Genome Biology 26:104 (Europe PMC full text XML) and 1 more record · DOI | Agrees | 7 | 0 | 0 |
Comparisons in An openly licensed benchmark… (6)
Comparisons in Livesey and Marsh 2025 (7)
| Protocol | Dataset | Metric | PHACTboost | BayesDel | 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 | 80.7 | 71.8 | PHACTboost |
| 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 | 70.7 | 57.1 | PHACTboost |
| 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 | 15.3 | 6 | PHACTboost |
| 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 | 66.8 | 56.8 | PHACTboost |
| 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 | 73.4 | 57.4 | PHACTboost |
| 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 | 71.9 | 57.1 | PHACTboost |
| 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 | 72.5 | 58.2 | PHACTboost |
What disagrees
- Other studies
- rank PHACTboost above BayesDel in 7 of 7 comparisons
- This study
- ranks BayesDel above PHACTboost in 4 of 5 comparisons
- Compared
- PHACTboost, BayesDel
- Study that disagrees
- An openly licensed benchmark and per-gene calibration map for missense pathogenicity predictors on activating cancer drivers, OncoCal repository, tables/tool_performance.tsv (per-tool AUROC and AUPRC by gene role)
- Other studies
- Livesey and Marsh 2025, Genome Biology 26:104 (Europe PMC full text XML), Livesey and Marsh 2025, Supplementary Material 2 (Tables S1-S8)
- Rule
- Ordering reversal; different tasks across studies
- Model identity
- Matched across studies partly through links not yet reviewed
The compared numbers
Each value links to its result record and source. Compare values within one protocol; the rule compares rankings, not raw values across protocols.
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.
Finding discrepancy-89cdb98a1172ce92 · All contested results · How findings are made and followed up