Vision-Based Genomic Model for Copy Number Variant Pathogenicity Prediction (opens in new tab)

Copy number variants (CNVs) are a major class of structural genomic alterations underlying rare disease, including neurodevelopmental delay and intellectual disability, yet predicting their pathogenicity remains challenging. Existing methods reduce CNVs to region-level numerical features, discarding the positional structure and cross-track patterns that expert clinical reviewers use to interpret genomic evidence. To address this, we introduce Tesseract for CNV, a track-based spatial represent...