Generative Models

Integrating multi-covariate disentanglement with counterfactual analysis on synthetic data enables cell type discovery and counterfactual predictions
CellDISECT is a powerful causal generative model that enhances single-cell analysis by disentangling variations, making counterfactual predictions, and achieving flexible fairness.
Stathis Megas, Arian Amani, Antony Rose, Olli Dufva, Kian Shamsaie, Hesam Asadollahzadeh, Krzysztof Polanski, Muzlifah Haniffa, Sarah Amalia Teichmann, Mohammad Lotfollahi
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Integrating multi-covariate disentanglement with counterfactual analysis on synthetic data enables cell type discovery and counterfactual predictions