BTEP Single Cell Seminar Series

The Trapnell Lab at the University of Washington's Department of Genome Sciences studies how genomes encode the program of vertebrate development and how that program goes awry in disease. We build new tools, technologies, and software for decoding this program from large-scale single-cell experiments.

The Bhattacharya Lab at the UCSF Parnassus Campus is focused on the functional role of monocyte-derived macrophages in the onset and persistence of fibrosis in the lung. We are addressing the following major questions, with a goal of discovering new targets for therapy for acute lung injury and fibrosis:

• What molecules released by monocyte-derived macrophages and other immune cells signal to and activate pro-fibrotic programs in parenchymal cell types such as fibroblasts and epithelial cells?
• What reciprocal signals derive from these parenchymal cells to modify the immune response?
• How can this pathologic crosstalk be reversed to combat fibrosis and restore lung health?

CellTypist was first developed as a platform for exploring tissue adaptation of cell types using scRNA-seq semi-automatic annotations. Now it's an open source tool for automated cell type annotations as well as a working group in charge of curating models and ontologies.

Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), have increased the resolution achieved in the study of cellular phenotypes, allowing measurements of thousands of different genes in thousands of individual cells. This has created an opportunity to begin understanding the dynamics of the prime biological processes undergone by cells, while requiring unique computational tools. In our lab, we develop novel and innovative computational methods for single-cell data analysis. - Theis Lab

Azimuth is a web application that uses an annotated reference dataset to automate the processing, analysis, and interpretation of a new single-cell RNA-seq experiment. Azimuth leverages a 'reference-based mapping' pipeline that inputs a counts matrix of gene expression in single cells, and performs normalization, visualization, cell annotation, and differential expression (biomarker discovery). All results can be explored within the app, and easily downloaded for additional downstream analysis. - Satija Lab

The development of Azimuth is led by the New York Genome Center Mapping Component as part of the NIH Human Biomolecular Atlas Project (HuBMAP).

This webinar will be recorded and made available on the BTEP web site: https://bioinformatics.ccr.cancer.gov/btep/btep-video-archive-of-past-classes/ within 48 hours after the event ends.