Shoutout to funders without whom this work would not have been possible @novo-nordisk.bsky.social @dg.dk

You can find many more details in the preprint biorxiv.org/content/10.1.... You can also try out DeepDive on your own data. You can find a tutorial on how to get started here: deepdive-tutorial.readthedocs.io/en/latest/. Reach out if you have questions or something does not work. 5/6

Finally, we apply DeepDive to islets (Sander lab), and dive into beta-cell subtypes linked to T2D. We id TFs differentially active between subtypes and after virtually perturbing disease status. TFs with counterfactual support more often have genetic and functional support! 4/6

Next, we turn counter-factual prediction and attempt to use the disentangled representations to predict the epigenome in an unseen covariate combination by virtually perturbing the observed covariates in real data. DeepDive outperforms baselines and achieves high accuracy. 3/6

To evaluate disentanglement, we analyzed collinear covariates in both simulated and real datasets. We found that regular statistical methods fail, as signal from one covariate leaks into another, but DeepDive accurately resolves which signal belongs to which covariate. 2/6