Paper from me @michecurtis@soumya_boston and co out now in @naturemethods! We now call the tool starCAT instead of *CAT but the strategy is the same: Build a catalog of ~50 interpretable T cell gene expression programs + use them to interpret new data https://t.co/qCJFcGg88B
So excited to share our latest with Betty Diamond and many colleagues from the AMP RA/SLE consortium, @NIH_NIAMS , and @NIAIDNews ! A large-scale blood and tissue atlas of Lupus Nephritis! https://t.co/c1SAlMnRcu
Thrilled to announce the publication of our latest manuscript on CD4 Trm cells in Nature Immunology! @NatImmunol
A huge thank you to our amazing team and collaborators for their incredible work!
https://t.co/Xm0ceymQnl
📣Excited to share my last postdoc paper with
@soumya_boston on eQTL mechanisms depending on where the RNA is in the cell! @BrighamResearch@broadinstitute
TL;DR:Early RNA eQTL variants in the nucleus and late RNA eQTL variants in the cytosol have distinct molecular mechanism🧵👇
Excited to tell you about VIMA (Variational Inference-based Microniche Analysis), our deep learning + stats hybrid for case-control analysis of multi-sample spatial molecular datasets. 🧵👇https://t.co/uEGIbNsNCZ. @soumya_boston , @broadinstitute , @BrighamResearch
Excited to share the final chapter my PhD research on @medrxivpreprint! eQTLs only explain 30% of GWAS loci and 11% of trait heritability. Here we investigate if epigenetic QTL can provide new insights at the remaining GWAS loci. https://t.co/vzkyjbTdkC
Science Immunology has just published our pooled in vivo CRISPR-screen (iCROP-seq). In this study we also address T cell plasticity in the kidney of ANCA-GN patients. Thanks to everybody involved in this study!
https://t.co/ae71AvI59v
AMP-RA study defining chromatin states in inflammatory #RheumatoidArthritis tissue is out! We argue: single cells can be grouped into chromatin classes, encompassing multiple transcriptional cells states. @NIH_NIAMS@broadinstitute@BrighamResearch
https://t.co/huAyX4FGyG
Excited to share our preprint proposing pgBoost, an eQTL-informed gradient boosting model that integrates scores from single-cell enhancer-gene linking methods and genomic distance to predict regulatory SNP-gene links (a key step in interpreting GWAS discoveries)!🧬
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@michecurtis and I are thrilled to share our preprint "Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions" from the @soumya_boston lab @BrighamResearch and @broadinstitute!
https://t.co/OexYxSnc3D
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