Integrative analysis of multi-modal single-cell data

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Cell identity, state, and function are multifaceted characteristics, determined by more than the transcriptome. As researchers look to gain deeper insights into cellular heterogeneity and uncover the functional mechanisms of disease, integrative analysis of multi-modal single cell data is emerging as a powerful approach to understand this complexity.

In this on-demand webinar, hear from Dr. Rahul Satija of the New York Genome Center as he introduces integrative multi-modal analysis with Seurat v4. Learn how to:
  • Analyze, explore, and integrate single cell datasets with Seurat v4, an updated version of the Satija Lab’s R toolkit
  • Leverage cutting-edge single cell approaches to analyze gene expression alongside protein levels, chromatin state, spatial location, and genetic perturbations
  • Perform integrative analysis of gene expression and chromatin accessibility data collected simultaneously from the same single cell