TCM visualizes trajectories and cell populations from single cell data.

Gong, Wuming; Kwak, Il-Youp; Koyano-Nakagawa, Naoko; Pan, Wei; Garry, Daniel J · Nat Commun · 2018

Level V

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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.

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