# Variant Prioritization

Super-enhancers could previously be defined only by stitching epigenomic peaks such as H3K27ac, so unprofiled cell states were out of reach and the underlying sequence grammar stayed unread. Borzoi-SE recasts super-enhancer discovery as cell-type-resolved genomic object detection over 524-kb sequences, returning super-enhancer probabilities and boundaries across 90 human cell and tissue lineages. On held-out chromosomes it reached a region-level PR-AUC of 0.643 and F1 of 0.498, against ceilings of about 0.34 and 0.15 for four fragment-based baselines; in silico ablation of the β-globin super-enhancer ranked HS2 as the dominant hub, and CRISPRi silencing of HS2 reduced chromatin accessibility across the locus by 35% to 85%.

Super-enhancers could previously be defined only by stitching epigenomic peaks such as H3K27ac, so unprofiled cell states were out of reach and the underlying sequence grammar stayed unread. Borzoi-SE recasts super-enhancer discovery as cell-type-resolved genomic object detection over 524-kb sequences, returning super-enhancer probabilities and boundaries across 90 human cell and tissue lineages. On held-out chromosomes it reached a region-level PR-AUC of 0.643 and F1 of 0.498, against ceilings of about 0.34 and 0.15 for four fragment-based baselines; in silico ablation of the β-globin super-enhancer ranked HS2 as the dominant hub, and CRISPRi silencing of HS2 reduced chromatin accessibility across the locus by 35% to 85%.

Many variants found in monogenic diabetes genes remain variants of uncertain significance because evidence is insufficient or conflicting. A pipeline trained on 7,706 confidently classified single nucleotide variants across 22 such genes reached ROC-AUC 0.9989 and AUPRC 0.9970 on 771 held-out variants, with recall 1.00 on the pathogenic class. Feature ablation showed that part of this accuracy reflects overlap with the ACMG criteria used to assign ClinVar labels, yet on non-missense variants, where computational evidence could not have been directly invoked, the model still beat a majority-class baseline, 99.0% versus 87.0%; it then ranked 6,306 uncertain variants with per-variant explanations.

Many variants found in monogenic diabetes genes remain variants of uncertain significance because evidence is insufficient or conflicting. A pipeline trained on 7,706 confidently classified single nucleotide variants across 22 such genes reached ROC-AUC 0.9989 and AUPRC 0.9970 on 771 held-out variants, with recall 1.00 on the pathogenic class. Feature ablation showed that part of this accuracy reflects overlap with the ACMG criteria used to assign ClinVar labels, yet on non-missense variants, where computational evidence could not have been directly invoked, the model still beat a majority-class baseline, 99.0% versus 87.0%; it then ranked 6,306 uncertain variants with per-variant explanations.