
Jun Cheng
@s6juncheng • 1,631 subscribers
Computational Biology | Machine learning research scientist at @GoogleDeepMind
Videos

Prioritizing and interpreting disease-associated genetic variants remains one of the greatest challenges in human genetics. Today, we’re thrilled to introduce AlphaGenome Atlas 🧬, a genome-wide platform providing precomputed predictions for the regulatory effects of all ~9 billion possible single-letter changes and >100M observed indels in the human genome. Here is what Atlas delivers: 1. Variant Prioritization via AVI To prioritize variants, we developed the AlphaGenome Variant Impact (AVI) score. AVI predicts a unified score per variant, where higher values indicate greater disruption. It achieves state-of-the-art performance across diverse benchmarks. As a proof-of-concept with our collaborators at Broad Institute, AVI prioritized a deep-intronic variant in DNM1, helping solve a previously unexplained rare epileptic encephalopathy case by revealing a brain-specific cryptic splice site. 2. Multi-Layer Molecular Interpretation Variant prioritization is only half the battle; researchers also need to understand why a variant matters. Atlas decomposes variant effects across multiple interpretable layers: •Feature Attributions which decompose each variant’s score into specific biological modalities driving the impact. •Cell-Type Specificity: Precomputed predictions with AlphaGenome across hundreds of biosamples reveal the exact cellular context in which a variant acts. •Regulatory Grammar: Over 2,600 de novo DNA motifs (and >250B genome-wide instances) show when variants directly disrupt critical regulatory binding "words". Explore the resource: 🌐 Interactive browser & precomputed data: - 🎥 Video: - 📖 Blog: - 📄 Preprint:
Jun Cheng11,434 次观看 • 6 天前
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