Ontology highlight
ABSTRACT:
SUBMITTER: Gulati GS
PROVIDER: S-EPMC7694873 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Gulati Gunsagar S GS Sikandar Shaheen S SS Wesche Daniel J DJ Manjunath Anoop A Bharadwaj Anjan A Berger Mark J MJ Ilagan Francisco F Kuo Angera H AH Hsieh Robert W RW Cai Shang S Zabala Maider M Scheeren Ferenc A FA Lobo Neethan A NA Qian Dalong D Yu Feiqiao B FB Dirbas Frederick M FM Clarke Michael F MF Newman Aaron M AM
Science (New York, N.Y.) 20200101 6476
Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular differentiation trajectories. However, inferring both the state and direction of differentiation is challenging. Here, we demonstrate a simple, yet robust, determinant of developmental potential-the number of expressed genes per cell-and leverage this measure of transcriptional diversity to develop a computational framework (CytoTRACE) for predicting differentiation states from scRNA-seq data. When applied ...[more]