Google DeepMind Releases AlphaGenome 2 for Cell-Type-Specific Variant Effects

Google DeepMind has released AlphaGenome 2, a conditional sequence-to-function DNA model that reads a 1 Mb DNA window plus a target cell state to predict variant effects in specific cell types, adapting to unseen single-cell datasets without fine-tuning. On TenK10K single-cell eQTLs it recovered 30% of causal variants at 90% precision versus 16% for fine-tuned AlphaGenome 1, with direction-of-effect recall rising from 23% to 43%. It is available through the AlphaGenome API for non-commercial research, with weights to come upon final publication.