TCM visualizes trajectories and cell populations from single cell data.

ABSTRACT: Profiling single cell gene expression data over specified time periods are increasingly applied to the study of complex developmental processes. Here, we describe a novel prototype-based dimension reduction method to visualize high throughput temporal expression data for single cell analyses. Our software preserves the global developmental trajectories over a specified time course, and it also identifies subpopulations of cells within each time point demonstrating superior visualization performance over six commonly used methods.

SUBMITTER: Gong W 

PROVIDER: S-EPMC6048168 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature