Genomics researcher: nobody has 'solved' variant prioritization, but old-score-only views are outdated
anshulkundaje · x · 2026-09-18
- Anshul Kundaje argues variant prioritization is very hard: anyone claiming to have "solved" it is lying, but those insisting old scores and models are all we need are frozen in time.
- Aggregate scores (CADD, AVI, GPN-STAR) remain useful coupled with context-specific effects, but collapsing multi-dimensional scores into one universal number loses information.
- Non-coding variant effects are highly cell-context specific — a weakness of DNA LMs not conditioned on cell context; supervised sequence-to-omics models learn that context-specific regulatory logic.
- AI agents and model interpretation open the door to reasoning over multi-dimensional variant effect scores without lossy summarization.
Related event: Stanford Expert's Deep Dive on DeepMind's AlphaGenome AVI Score(29 posts)→
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