Excited to share DeepDive, a generative model for disentangling covariate effects in snATAC-seq developed by the amazing @afmoeller. DeepDive enables deeper understanding of a dataset by separating the effects of known and unknown covariates. Here are some highlights. 1/6
📢 PREPRINT ALERT 📢 Clustering cells is a key step in most scRNA-seq analysis workflows. It's hard, and harder with batch effects.
Our take on the problem, JOINTLY, use a hybrid linear and non-linear NMF. The non-linearity gives performance, the linearity gives interpretability
How to build a mucociliary epithelium (MCE)? Lesson from frogs!🐸
Extremely happy to share our collaborative work with @kedar_natarajan lab, where we profiled developing Xenopus laevis MCE from pluripotent to specialized cell types by scRNAseq. 🧵(1/8):
https://t.co/MlPq1IJftP
A grand challenge in genomic medicine is predicting how disease risk variants impact gene regulation in human cells. Towards a Human Gene Regulation Map the @novonordiskfond Center @broadinstitute has openings in 8 labs bridging Boston & Denmark 🧵 👇1/3
https://t.co/6l3a1SxEeC