Analyzing single-cell landscapesby Liz Entman Nov. 30, 2018, 8:42 AM
Single-cell RNA sequencing is a powerful tool for studying cellular diversity, for example in cancer where varied tumor cell types determine diagnosis, prognosis and response to therapy. Single-cell technologies generate hundreds to thousands of data points per sample, generating a need for new methods to define cell populations across different single-cell landscapes.
Qi Liu, PhD, Ken Lau, PhD, and colleagues have developed a new tool, sc-UniFrac, to quantify diverse cell types in single-cell studies. The tool compares hierarchical trees that represent single-cell landscapes and allows cells that drive differences to be identified as unbalanced branches on the trees.