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What a joy it's been to work on this with Eva Holtkamp Oliver Stegle gagneurlab and the rest of the team at DKFZ, TUM, and @AIHCluster Very proud of these advances in using deep learning to model rare variants in association genetics and prediction of high-risk individuals

Wanna do Rare Variant Association Testing powered by deep learning? See Brian Clarke & my poster PB4113 Fr. 3pm on DeepRVAT. New results on phenome-wide application, binary traits, 10x faster than SOTA Oliver Stegle & gagneurlab collab. Update: shorturl.at/egtB0 #ASHG23

📢 PhD/Postdoc opportunities in our group: - tinyurl.com/ml-spatial-data - tinyurl.com/grn-multi-omics - tinyurl.com/causal-single-… Join our vibrant research community in Heidelberg if you are excited about research at the interface of statistics, machine learning and life sciences! Plz RT

🧵1/10 We’re thrilled to share our latest paper, Bicycle, a novel approach for inferring cyclic causal relationships from observational and interventional data! This work addresses a critical gap in understanding complex biological networks.

Big thanks to the DKFZ PR department for this writeup of our results suitable for a general audience

Herzlichen Dank an die Stabstelle für Öffentlichkeitsarbeit des DKFZ für diese allgemeinverständliche Pressemitteilung über unsere Arbeit

#GPMelt users, it was fantastic meeting so many of you at my #HUPO2024 poster!🎊 As discussed, the revised GPMelt code is now on GitLab. Also, check out the GPMelt website to dive into the model—no advanced maths required! 💻🔍 #Proteomics All links here: linktr.ee/CecileCADS