Join us for the 17th Berlin Summer Meeting – AI’s Adventures in Genomics, 6-7 June 2024 to explore the latest advancements, challenges, and prospects in harnessing AI for biomedical research and applications! Registration: https://t.co/Jtxo0Zjrkf #mdcBerlin
Our algorithm epiAneufinder for calling copy number variations in single-cells from scATACseq is out! https://t.co/OIQy53I1ta Now you can add CNV information to any scATAC-seq or multiome dataset without the need of another data modality or reference diploid sample. Try it out!
#NewPreprint alert 📢
Thrilled to share our work on multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution
https://t.co/x47Uh4qUaT
paving the way towards in vitro epidemiology.
Eager to know more? 👉🧵
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1/7 How do genetic variants affect co-expression patterns and how can this help us to interpret consequences of GWAS hits? In our latest preprint, we use scRNAseq to find such associations by mapping co-expression QTLs (co-eQTL)! https://t.co/VK7msVwn4V
Genetic variation can affect co-expression relationships, as we see in a meta-analysis of single-cell eQTL data, now out: https://t.co/NPDV5DUmKE. We observe colocalisation between a rheumatoid arthritis locus and effects on co-expression of T cell activation genes with RPS26.
Happy that our preprint about co-expression QTL identification in scRNA-seq cohorts is out. Had a lot of fun in this collaboration and very proud about the figures (credit for them goes to @Shuangli1330)
1/7 How do genetic variants affect co-expression patterns and how can this help us to interpret consequences of GWAS hits? In our latest preprint, we use scRNAseq to find such associations by mapping co-expression QTLs (co-eQTL)! https://t.co/UvpSyxLmAO
Interested in how atrial fibrillation associated genetic variation impacts transcript and protein levels in the human heart? We link genetic variation to disease through gene networks. Great colab @CompHealthMuc@UCCS_HH https://t.co/bmomEZxasX
Wondering what you can learn from integrating DNA methylation and genetics? @johannhawe and @schmidkathe (@ICBMunich) et al did a great job in identifying GRNs for GWAS loci and finding cell type specific meQTL. Great collaboration, very happy that this is out now!
Very excited about my first publication. If you are looking for a fast and user-friendly tool to design your next multi-sample scRNA-seq experiment, try scPower!
Check out our new integrative multiOMICs approach with genomics, transcriptomics, and proteomics of human atrial tissue. regulatory genetic variants and their downstream consequences on transcriptome, proteome and atrial fibrillation: https://t.co/yMyHfqm5qo
Our preprint on experimental design & power analysis for multi-sample #SingleCell analysis is out https://t.co/QgRLZkHozP! Apply our R package https://t.co/zUW1OFVd0Y or use our website https://t.co/D2MdijWR6R @heinig_matthias@fabian_theis@Binder_Lab@LickertHeiko @ICBmunich