@ludefranke.bsky.social
We studied non-coding somatic mutations in WGS data of 24,000 cancer patients. We employed sequence-based models to identify promotors, enriched for somatic variants that are predicted to affect expression. A great collaboration with the teams of Emile Voest, Bas van Steensel and Jeroen de Ridder!
We are excited to share our manuscript “Identification of (ultra-)rare functional promoter mutations in cancer using sequence-based deep learning models” (www.medrxiv.org/content/10.1...). (1/16) 🧵
May 7, 2025 at 8:03 AM
We studied non-coding somatic mutations in WGS data of 24,000 cancer patients. We employed sequence-based models to identify promotors, enriched for somatic variants that are predicted to affect expression. A great collaboration with the teams of Emile Voest, Bas van Steensel and Jeroen de Ridder!