An interesting "what have we been doing all these years?" result from this paper is how sub-optimal the widely-used uniform sampling scheme can be (cluster all @50%, sample from all clusters equally). In contrast, strategies that account for the relative differences in cluster size improve val loss
Very cool paper from Eddie Park and Yi Xing studying the relationship between intron retention QTLs and expression QTLs. Predictably, genetically regulated intron retention can cause changes in gene expression via nonsense-mediated decay (NMD). www.biorxiv.org/content/10.1...
Are you using any of our factor models, such as MOFA? 🛵
You might’ve found it challenging to tailor them to your specific use cases - not anymore!
Introducing MOFA-FLEX: a flexible, modular factor analysis framework designed for customizable modeling across diverse multi-omics data scenarios. 1/n
Single task, lightweight, short-context bp res. profile models often perform on par or outperform current large, multi task, long context models on counterfactual prediction. Much to do to improve.
Bonus: robust, efficient interpretation of syntax
Great collab with @jengreitz.bsky.social lab.
We are the Stegle Lab: A bioinformatics group advancing computational methods to study molecular variations and their impact on phenotypes. We are jointly hosted at the German Cancer Research Center (@dkfz.bsky.social) and the European Molecular Biology Laboratory (@embl.org) in Heidelberg, Germany.
📢 new preprint alert: So so excited to share our analysis on the impact of common and rare variants on single-cell gene expression in blood, using WGS and scRNA-seq data from nearly 2,000 individuals and 5.4m cells as part of TenK10K phase 1 🧬 www.medrxiv.org/content/10.1...
🧵👇 (1/n)