Single-cell transcriptional diversity is a hallmark of developmental potential
Abstract
A detailed knowledge of cell differentiation hierarchies is important for understanding diverse biological processes such as organ development, tissue regeneration, and cancer. Single-cell RNA sequencing can help elucidate these hierarchies, but it requires reliable computational methods for predicting cell lineage trajectories. Gulati et al. developed CytoTRACE, a computational framework based on the simple observation that transcriptional diversity—the number of genes expressed in a cell—decreases during differentiation. CytoTRACE outperformed other methods in several test cases and was successfully applied to study cellular hierarchies in healthy and tumor tissue.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 24, 2020
- Source ID
- 10.1126/science.aax0249
Entities
People
- Aaron M. Newman
- Angera H Kuo
- Anjan Bharadwaj
- Anoop Manjunath
- Dalong Qian
- Daniel J Wesche
- Feiqiao Yu
- Ferenc A. Scheeren
- Francisco Ilagan
- Frederick M Dirbas
- Gunsagar S Gulati
- Maider Zabala
- Mark J. Berger
- Michael F Clarke
- Neethan A Lobo
- Robert W. Hsieh
- Shaheen S Sikandar
- Shang Cai
Organizations
- Chan Zuckerberg Biohub
- Leiden University Medical Center
- Ludwig Institute for Cancer Research
- National Cancer Institute
- National Science Foundation
- Stanford University
- The Breast Cancer Research Foundation
- United States Department of Defense
- Westlake University