Seurat v5: Cross-Modality Mapping and Large-Scale Clustering of Single-Cell Data

Explore a comprehensive lecture on advanced single-cell data analysis techniques presented at the Broad Institute. Delve into the innovative 'bridge integration' method for integrating single-cell datasets across modalities using multiomic data as a molecular bridge. Learn how this approach enables accurate integration of transcriptomic data with various single-cell measurements, including chromatin accessibility, histone modifications, DNA methylation, and protein levels. Discover the power of combining dictionary learning and sketching techniques in 'atomic sketching integration' to enhance computational scalability and enable unsupervised clustering of massive scRNA-seq datasets. Gain insights into the latest developments in Seurat v5 toolkit, which expands the utility of single-cell reference datasets and facilitates comparisons across diverse molecular modalities. Understand how these cutting-edge methods are revolutionizing the field of single-cell analysis and opening new avenues for biological research.

MIA: Yuhan Hao, Seurat v5, cross-modality mapping and large-scale clustering of single-cell data