DeepMind releases AlphaGenome 2, predicting variant effects by cell type

1. 20:09
   The Decoder

   Google Deepmind shifts genomics AI from bulk tissue predictions to single cell type resolution with AlphaGenome 2

   Google DeepMind released AlphaGenome 2, a conditional genomics model trained on more than 107 million individual cell profiles from 68 human and mouse tissues that predicts variant effects for specific cell types rather than across many tissues at once. On the TenK10K benchmark of 28 primary immune cell types it identified about 30 percent of causal variants and correctly predicted up- or down-regulation in 43 percent of cases, versus 16 and 23 percent for a fine-tuned AlphaGenome 1. It is available for noncommercial research via API, with commercial access through a closed preview, and is not approved for clinical diagnostics.

2. 04:51
   MarkTechPost

   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.

1. 23:00
   Google DeepMindFeatured

   AlphaGenome 2: Deciphering how cells read DNA to better understand disease

   Google DeepMind announced AlphaGenome 2, a conditional DNA sequence model trained on over 107 million individual cell profiles across 68 tissues that predicts how genetic variants affect gene expression in specific human cell types and states. The model identified nearly twice as many causal variants (30% vs. 16%) and directional gene effects (43% vs. 23%) as the original AlphaGenome fine-tuned on single-cell data on the TenK10K immune cell dataset, and can generalize to unseen single-cell experiments without retraining. It is available for non-commercial research via the AlphaGenome API and in private preview for commercial research.

2. 23:00
   The Verge · AI

   Google’s AlphaGenome 2 zooms in on the cellular roots of disease

   Google DeepMind unveiled AlphaGenome 2, a successor to last year's AlphaGenome that predicts how genetic variants affect individual cell types and states, trained on more than 100 million cell profiles across 68 tissues. Google says the model identifies nearly twice as many variants that can change gene expression as its previous state-of-the-art model, and can make predictions about new cell types and states without retraining. It is available for non-commercial research via the AlphaGenome API from today, with a limited private preview for commercial research.

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