Katharina Schmid retweeted
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: bit.ly/bsmAI #mdcBerlin
Katharina Schmid retweeted
Our algorithm epiAneufinder for calling copy number variations in single-cells from scATACseq is out! bit.ly/epiAneufinder 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!
Katharina Schmid retweeted
#NewPreprint alert 📢
Thrilled to share our work on multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution
biorxiv.org/content/10.1101/…
paving the way towards in vitro epidemiology.
Eager to know more? 👉🧵
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Katharina Schmid retweeted
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)! doi.org/10.1186/s13059-023-0…
Katharina Schmid retweeted
Genetic variation can affect co-expression relationships, as we see in a meta-analysis of single-cell eQTL data, now out: genomebiology.biomedcentral.…. We observe colocalisation between a rheumatoid arthritis locus and effects on co-expression of T cell activation genes with RPS26.
Congratulations Dr. @Shuangli1330 ! It was a big honor to stand next to you at this special moment.
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)! biorxiv.org/content/10.1101/…
Katharina Schmid retweeted
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 nature.com/articles/s41467-0…
Katharina Schmid retweeted
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!
Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function (Hawe et al.) go.nature.com/3JNFSfM
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!
scPower, our analytic framework for design and power analysis of multi-sample scRNA-seq experiments, is out @NatureComms . Code and GUI scpower.helmholtz-muenchen.d…. Great work by @schmidkathe @heinig_matthias @fabian_theis @LickertHeiko @Binder_Lab rdcu.be/cBryR
Katharina Schmid retweeted
Woohoo!Our preprint on #network inference for multi-omics data using data-driven priors is out on @biorxivpreprint @biorxiv_bioinfo Check it out here:bit.ly/3c0blZR Big Thanks! to all involved! @ashissaha123 @alexisjbattle @heinig_matthias @fabian_theis @MartinaNurasyid
Katharina Schmid retweeted
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: doi.org/10.1101/2020.04.06.0…
Our preprint on experimental design & power analysis for multi-sample #SingleCell analysis is out biorxiv.org/cgi/content/shor…! Apply our R package github.com/heiniglab/scPower or use our website scpower.helmholtz-muenchen.d… @heinig_matthias @fabian_theis @Binder_Lab @LickertHeiko @ICBmunich