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Contested result

ChromBPNet and Caduceus: GUANinE v1.1 reveals complementarity of supervised and genomic language models and Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants disagree

  • Low severity
  • Not yet reviewed
  • two-study-conflict
  • unknown

GUANinE v1.1 reveals complementarity of supervised and genomic language models ranks Caduceus above ChromBPNet in 6 of 6 comparisons; Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants ranks ChromBPNet above Caduceus in 4 of 4 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 ChromBPNet above Caduceus in 4 of their 10 comparisons and Caduceus higher in 6. Of those papers, GUANinE v1.1 reveals complementarity… ranks Caduceus higher on its own (6 of 6).

Papers grouped by which system they rank higher: ChromBPNet or CaduceusRank ChromBPNet higher: Comparative Analysis of Deep Learning…. Rank Caduceus higher: GUANinE v1.1 reveals complementarity…. Mixed: none.Rank ChromBPNet higherMixedRank Caduceus higherComparative Analysisof Deep Learning…Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory VariantsGUANinE v1.1 revealscomplementarity…GUANinE v1.1 reveals complementarity of supervised and genomic language models
  • Rank ChromBPNet higher (1): Comparative Analysis of Deep Learning…
  • Rank Caduceus higher (1): GUANinE v1.1 reveals complementarity…
  • 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.

Comparisons in which each paper scores ChromBPNet or Caduceus higherGUANinE v1.1 reveals complementarity…: ChromBPNet higher in 0, Caduceus higher in 6, 0 ties. Comparative Analysis of Deep Learning…: ChromBPNet higher in 4, Caduceus higher in 0, 0 ties.GUANinE v1.1 reveals complementarity…GUANinE v1.1 reveals complementarity of supervised and genomic language models6 Caduceus higher6Comparative Analysis of Deep Learning…Comparative Analysis of Deep Learning Models for Predicting Causative Regulatory Variants4 ChromBPNet higher4
ChromBPNet higherTieCaduceus higherNumbers are counts of comparisons; the outlined bar is the paper that disagrees.
Comparisons in GUANinE v1.1 reveals complementarity… (6)
ProtocolDatasetMetricChromBPNetCaduceusHigher
GUANinE v1.1 ccre-propensity, Spearman rho x100 (Table 2)GUANinE ccre-propensity test setSpearman (GUANinE v1.1 test set), unitless40.441.3Caduceus
GUANinE v1.1 cons100, Spearman rho x100 (Table 2)GUANinE cons100 test setSpearman (GUANinE v1.1 test set), unitless41.562.4Caduceus
GUANinE v1.1 cons30, Spearman rho x100 (Table 2)GUANinE cons30 test setSpearman (GUANinE v1.1 test set), unitless47.874.4Caduceus
GUANinE v1.1 dnase-propensity, Spearman rho x100 (Table 2)GUANinE dnase-propensity test setSpearman (GUANinE v1.1 test set), unitless41.543Caduceus
GUANinE v1.1 gpra-c, Spearman rho x100 (Table 2)GUANinE gpra-c test setSpearman (GUANinE v1.1 test set), unitless71.172.4Caduceus
GUANinE v1.1 gpra-d, Spearman rho x100 (Table 2)GUANinE gpra-d test setSpearman (GUANinE v1.1 test set), unitless74.976Caduceus
Comparisons in Comparative Analysis of Deep Learning… (4)
ProtocolDatasetMetricChromBPNetCaduceusHigher
Allelic reporter effect correlation in HeLa (Manzo et al. 2025 Table 1)HeLa regulatory variant reporter data (Manzo et al. 2025)Pearson (predicted versus measured log2 fold-change of variant effect), unitless0.2890.02ChromBPNet
Allelic reporter effect correlation in HepG2 (Manzo et al. 2025 Table 1)HepG2 regulatory variant reporter data (Manzo et al. 2025)Pearson (predicted versus measured log2 fold-change of variant effect), unitless0.2950.108ChromBPNet
Allelic reporter effect correlation in K562 (Manzo et al. 2025 Table 1)K562 regulatory variant reporter data (Manzo et al. 2025)Pearson (predicted versus measured log2 fold-change of variant effect), unitless0.2870.133ChromBPNet
Allelic reporter effect correlation in NPC (Manzo et al. 2025 Table 1)NPC regulatory variant reporter data (Manzo et al. 2025)Pearson (predicted versus measured log2 fold-change of variant effect), unitless0.080.023ChromBPNet

What disagrees

studies
2
Compared
ChromBPNet, Caduceus
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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