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Jesper Madsen @jespergrud.bsky.social · 07/10/2025

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

Jesper Madsen @jespergrud.bsky.social · 07/10/2025

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

biorxiv.org

Disentangling covariate effects on single cell-resolved epigenomes with DeepDive

Understanding the effects of individual biological factors from single cell-resolved epigenomic data is hindered by multicollinearity, particularly in human cohorts. We introduce DeepDive, a novel dee...

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Jesper Madsen @jespergrud.bsky.social · 07/10/2025

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

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Jesper Madsen @jespergrud.bsky.social · 07/10/2025

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

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Jesper Madsen @jespergrud.bsky.social · 07/10/2025

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

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Jesper Madsen @jespergrud.bsky.social · 07/10/2025

Excited to share DeepDive, a generative model for disentangling covariate effects in snATAC-seq developed by the amazing @andreasfm.bsky.social. DeepDive enables deeper understanding of a dataset by separating the effects of known and unknown covariates. Here are some highlights. 1/6

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Reposted by Jesper Madsen

Ravnskjaer_lab @ravnskjaer-lab.bsky.social · 03/03/2025

Check out our latest paper now online at Cell Metabolism: Hepatic stellate cells regulate liver fatty acid utilization via plasmalemma vesicle-associated protein. Amazing work by Daniel, Jasmin, Christian, Peter, Oliver from @ravnskjaer_lab, and many more 🏆💐♥️ www.cell.com/cell-metabol...

cell.com

Hepatic stellate cells regulate liver fatty acid utilization via plasmalemma vesicle-associated protein

Hansen et al. show that the hepatic stellate cell-expressed plasmalemma vesicle-associated protein is required for the normal switch from carbohydrate to lipid utilization during fasting. This reveals...

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Jesper Madsen @jespergrud.bsky.social · 01/02/2025

Preprint alert! We used snRNA-seq on adipose tissue from a longitudinal cohort of people undergoing surgury-induced weight loss. True ATLAS team effort We found dramatic changes in immune and progenitor compartments. Give it a read and let us know what you think. www.biorxiv.org/content/10.1...

biorxiv.org

Single cell-resolved transcriptional dynamics of human subcutaneous adipose tissue during lifestyle- and bariatric surgery-induced weight loss

During sustained weight gain, human white adipose tissue undergoes dramatic remodeling that may compromise adipose tissue function and lead to obesity comorbidities such as cardiometabolic disease. Th...

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