Data Analysis Unit The main goal of the Data Analysis Unit is to provide state-of-the art bioinformatics and biostatistics tools/methods for the construction of a dynamic and multidimensional atlas of colorectal pre-cancer lesions at single-cell resolution. Focusing on single-cell expression profiles from cell populations in suspension, and imaging techniques that preserve tissue spatial information, we will characterize the landscape of gene mutations, cellular composition, cell-microbe-immune interactions, and progression trajectories in unique surgically resected specimens, which may comprise the full normal-adenoma-to-cancer sequence as well as in collected specimens of normal colonic mucosa, early, and late adenomas. We will identify cellular, spatial, functional, and microbial biomarkers associated with progression and build a predictive model of colorectal neoplastic transformation.
| Chen, Bob; Herring, Charles A; Lau, Ken S (2018) pyNVR: Investigating factors affecting feature selection from scRNA-seq data for lineage reconstruction. Bioinformatics : |
| Liu, Qi; Herring, Charles A; Sheng, Quanhu et al. (2018) Quantitative assessment of cell population diversity in single-cell landscapes. PLoS Biol 16:e2006687 |
