Innovating computational methods to discover grammars of gene regulation in T cells

To achieve our lab’s central goal, which is to better understand the chromatin biology of T cells in health and disease, we also innovate computational techniques to fully understand the complexity of multidimensional epigenomic datasets in T cells. We devised a computational workflow called PRISM to quantify cell-to-cell chromatin accessibility variation at transcription factor binding sites across individual cells (Cai et al., 2018). We also participated in the development of TooManyCells, which is a divisive hierarchical spectral clustering method. Our contribution to the single-cell genomic field was recently recognized by a Chan Zuckerberg Initiative award.