Exploring genetic interaction manifolds constructed from rich single-cell phenotypes
Abstract
Mapping of genetic interactions (GIs) is usually based on cell fitness as the phenotypic readout, which obscures the mechanistic origin of interactions. Norman et al. developed a framework for mapping and understanding GIs. This approach leverages high-dimensional single-cell RNA sequencing data gathered from CRISPR-mediated, pooled perturbation screens. Diverse transcriptomic phenotypes construct a “manifold” representing all possible states of the cell. Each perturbation and GI projects the cell state to a particular position on this manifold, enabling unbiased ordering of genes in pathways and systematic classifications of GIs.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Aug 23, 2019
- Source ID
- 10.1126/science.aax4438
Entities
People
- Albert Xu
- Alex Y Ge
- Jonathan Weissman
- Joseph M Replogle
- Luke A Gilbert
- Marco Jost
- Max A Horlbeck
- Thomas M Norman
Organizations
- Damon Runyon Cancer Research Foundation
- Howard Hughes Medical Institute
- National Institutes of Health
- University of California