From Cancer to COVID: Dissecting Human Immunology with Emergent Technology


  • Anthony R. Cillo, Ph.D. Postdoctoral Fellow, Vignali Lab, Dept. of Immunology and Tumor Microenvironment Center, University of Pittsburgh

The widespread adoption of single-cell transcriptomic technology coupled with the development of a robust bioinformatics ecosystem has enabled new biological insights across disciplines. This workshop will illustrate how to leverage the inherent complexity in single-cell datasets to arrive at biological conclusions. We will utilize human immunologic single-cell datasets to highlight automated cell type identification, characterization of putative intercellular communication networks, and applications of machine learning-based approaches across patient samples to extract biological insight. Following this workshop attendees will have a better understanding of the ways in which immunology can be understood through analysis of single-cell transcriptomic datasets.

Veritas se revelet: Computational Population Discovery and Sorting for Multi-Omics Analysis


  • Tim Crawford, Ph.D.

Multiomic Analysis of T Cell Development


  • Aaron Streets, Ph.D., Assistant Professor, Bioengineering, UC Berkeley
  • Miguel Tam, Ph.D., Director, Strategic Marketing, BioLegend

Dr. Aaron Streets of UC Berkeley will introduce a new computational tool that was used to map T cell development in the thymus with single-cell multiomic analysis, as recently published in Nature Methods.