Discover and read the best of Twitter Threads about #scRNA
Most recents (5)
Excited to share our paper in @NatureComms where we present the 1M-scBloodNL study in which we profiled 1.3M immune cells from 120 healthy individuals, longitudinally exposed to 3 different pathogens doi.org/10.1038/s41467… @UMCGgenetica #scRNA 1/8
We mapped differential expression, cis-eQTLs and response-QTLs in 6 major immune cell types and 10 subcell types. This indicated that the genetic control of the gene expression response upon pathogen stimulation was more cell-type- than pathogen-specific. 2/8
Always wondered how and in which context genetics controls downstream gene expression, but without having to test dozens of specific stimuli to figure it out? Here we show how co-expression QTL analysis on whole pathogen-stimulated immune cells can do so! 3/8
Excited to share that our @NatureBiotech paper with Aviv Regev on Multicellular Programs (MCPs) is now out with a fully automated data-driven method to identify MCPs from #singlecell or spatial data #behindthepaper: go.nature.com/3iQ8fgW nature.com/articles/s4158… (1/19) 
Gene programs are often studied within a cell, with each cell considered an “independent entity”. However, cells from the same niche/tissue/organism are not independent, but share external signals, genetic background/lineage, and can directly impact one another. (2/19)
Here we define “Multicellular Programs (MCPs)” as different sets of genes working in concert across different cell types. (3/19)
Excited to share our new #method, scDRS, for associating **individual cells** to disease by integrating #scRNA-seq + #GWAS, providing #polygenic disease risk enrichment beyond tissues or cell types.
biorxiv.org/content/10.110…
biorxiv.org/content/10.110…
scDRS assesses excess expression of a set of putative disease genes constructed from GWAS, using an appropriately matched empirical null distribution to compute p-values. (2/n)
We applied scDRS to GWAS from 74 diseases and complex traits (average N=341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs, including the amazing Tabula Muris Senis mouse atlas and Tabula Sapiens human atlas @czbiohub. (3/n)
New insights into SARS-CoV-2 immune evasion
#SARS-CoV-2 #mutations can lead to antibody #escape. What about T cells? In our study in @SciImmunology we report how mutated epitopes evade T cell responses.
immunology.sciencemag.org/content/6/57/e… 1/7
#SARS-CoV-2 #mutations can lead to antibody #escape. What about T cells? In our study in @SciImmunology we report how mutated epitopes evade T cell responses.
immunology.sciencemag.org/content/6/57/e… 1/7
Using deep viral sequencing we identified low-frequency mutations in experimentally validated CD8 T cell epitopes of SARS-CoV-2, some of which were found as fixed mutations in global virus sequences from @GISAID. 2/7
Guided by binding predictions we selected epitopes and #mutants for further biochemical investigations by cell-free MHC-I binding assays. These analyses suggested that single amino acid changes impair binding to MHC-I molecules. 3/7
We developed Visualization in Plugin on top of #cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format for #singlecell #rnaseq dataset #scRNAseq #scanpy
The preprint is available here
@cellxgene VIP unleashes full power of interactive visualization, plotting and analysis of #scRNA-seq data in the scale of millions of cells biorxiv.org/content/10.110…
@cellxgene VIP unleashes full power of interactive visualization, plotting and analysis of #scRNA-seq data in the scale of millions of cells biorxiv.org/content/10.110…
Want to play with cellxgene VIP live? Demo is here
cellxgenevip-ms.bxgenomics.com
Dataset: MS brain #snRNAseq dataset by @schirmerlab and #RowitchLab
cellxgenevip-ms.bxgenomics.com
Dataset: MS brain #snRNAseq dataset by @schirmerlab and #RowitchLab
