The Centers of Excellence in Genomic Science (CEGS) program is run by the National Human Genome Research Institute, and supports formation of multi-investigator, interdisciplinary research teams to develop novel and innovative genomic technologies. Our center was established in the summer of 2020, and represents a collaborative effort between six institutions in New York City.
While recent years have witnessed transformative advances in single-cell RNA sequencing (scRNA-seq), information from a single modality is often insufficient to yield deep biological insight into cellular state and identity that is necessary for devising effective, personalized approaches to treatment. In response, the mission of our Center is to develop a comprehensive suite of technologies and analytical methods to measure and integrate the molecular and environmental determinants of cellular identity. We will develop tools to simultaneously measure and harmonize epigenetic state, transcriptomic output, protein levels, lineage, and spatial environment across individual cells. Our Center will address critical challenges in data integration, and produce software, protocols, and strategies that will be applicable to diverse biological systems and will be shared broadly with the community.
Education and Outreach
As our Center hopes to develop broadly applicable genomic methods, we also aim to ensure that our software and technologies are accessible to a broad spectrum of researchers, including outside of the genomics community. While our center is just starting, please check back here for new events, such as our Single Cell Genomics Day practical workshop, CITE-seq and Spatial Transcriptomics webinars, and Next-Generation Genomics conference.
For additional updates, please feel free to follow our twitter account:
Resources
Seurat: R toolkit for the analysis, interpretation, and integration of single-cell data
Azimuth: Fast mapping of query datasets onto a multimodal PBMC reference
CITE-seq: Multimodal single-cell phenotyping
Splotch: Hierarchical generative probabilistic modeling of Spatial Transcriptomics
CellMine: Interactive visualization of single-cell genomes
Randomly: Denoising scRNA-seq with Random Matrix Theory
News
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RT @JBlairSci: Excited to see this out in the world! 🧵 https://t.co/ENLGtcCEWq
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RT @satijalab: We are excited to introduce Phospho-seq, our approach for profiling intracellular protein and cell signaling dynami… https://t.co/1z8c9Fgr8I
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RT @satijalab: Interested in single cell genomics but need help getting started? Check out the full agenda for our Single Cell Gen… https://t.co/nwtOHVQ7tU
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RT @satijalab: We've been working on Seurat v5 for two years and are excited to share it with you soon! In a webinar w/… https://t.co/QrlxB62dRa
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1/8 Today we highlight awesome work from @SchragaSchwartz lab at @WeizmannScience exploring how and why m6A is depo… https://t.co/hDFH3cUxzQ