BTEP Single Cell Seminar Series

Please note: Registration is required to get the Meeting Link for this event. Please pre-register.

BTEP and the Single Cell and Spatial Transcriptomics Interest Group jointly present:

Quantifying spatiotemporal dynamics during embryogenesis is crucial for understanding congenital diseases. We developed Spateo (https://github.com/aristoteleo/spateo-release), a 3D spatiotemporal modeling framework, and applied it to a 3D mouse embryogenesis atlas at E9.5 and E11.5, capturing eight million cells. Spateo enables scalable, partial, non-rigid alignment, multi-slice refinement, and mesh correction to create molecular holograms of whole embryos. It introduces digitization methods to uncover multi-level biology from subcellular to whole organ, identifying expression gradients along orthogonal axes of emergent 3D structures, e.g., secondary organizers such as midbrain-hindbrain boundary (MHB). Spateo further jointly models intercellular and intracellular interaction to dissect signaling landscapes in 3D structures, including the zona limitans intrathalamica (ZLI). Lastly, Spateo introduces “morphometric vector fields” of cell migration and integrates spatial differential geometry to unveil molecular programs underlying asymmetrical murine heart organogenesis and others, bridging macroscopic changes with molecular dynamics. Thus, Spateo enables the study of organ ecology at a molecular level in 3D space over time.

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.