PQG Seminar

Cell dynamics across various time scales and spatial coordinates

In biological processes like development and disease progression, cells differentiate into various cell types. At the time scale of cell divisions, lineage tracing technologies make it possible to reconstruct the cell division history, and learn how cell types are formed through generations of cell divisions for one individual. At a larger time scale, scRNA-seq data of a number of individuals under different conditions or developmental time points are obtained, which allows for systematic analysis of gene expression changes across conditions and the prediction of data under unseen conditions. Cell temporal processes are closely coupled with spatial organization of cells, and thus the two aspects are best considered in the same picture. After cell division, cells can migrate to different locations in the tissue. We leverage temporal information in tackling current challenges in spatial data analysis, including cell type deconvolution and mapping between scRNA-seq and spatial data. Finally, we have developed a series of de novo simulation tools which help with evaluating computational methods for the problems above and beyond. I will introduce these simulation tools which can be useful for a wide range of computational tasks for single cell omics.