Google DeepMind releases AlphaGenome 2 for cell-type-specific variant prediction

Google DeepMind has released AlphaGenome 2, a genomics model that predicts how DNA variants affect specific human cell types and finds nearly twice as many relevant gene changes as its predecessor. Trained on more than 107 million individual cell profiles from 68 tissues in humans and mice, it takes a cell's biological state as an extra input instead of predicting broadly across many tissues at once.

Google DeepMind released AlphaGenome 2, a conditional sequence-to-function DNA model that reads a 1 Mb DNA window plus a target cell state and predicts variant effects for one cell type per call. On TenK10K single-cell eQTLs across 28 immune cell types, causal variant recall at 90% precision rose from 16% for fine-tuned AlphaGenome 1 to 30%, and direction-of-effect recall rose from 23% to 43%. The model is available through the AlphaGenome API for non-commercial research, with weights promised upon final publication and commercial use in private preview.

Google DeepMind announced AlphaGenome 2, a next-generation DNA sequence model that predicts how DNA sequences and their variants affect specific human cell types. Trained on more than 107 million individual cell profiles across 68 tissues, the conditional model identified nearly twice as many expression-changing variants as the previous model, and on the TenK10K immune cell dataset it recovered 30% of causal variants versus 16% for the original AlphaGenome fine-tuned on single-cell data. It is available for non-commercial research via the AlphaGenome API and in private preview for commercial research.

Google DeepMind has unveiled AlphaGenome 2, a successor to last year's AlphaGenome that predicts how genetic variants affect individual cell types and states rather than broad tissue averages. Trained on more than 100 million individual cell profiles across 68 tissues, the model identifies nearly twice as many variants that can change gene expression as the previous state-of-the-art model, and can make predictions about new cell types and biological states without retraining. Google is offering it for non-commercial research via the AlphaGenome API from today, with a limited private preview for commercial use; DeepMind's Žiga Avsec said its finer predictions are more computationally expensive, so it will not replace AlphaGenome soon.