Mapping transcriptomic vector fields of single cells
Howard Hughes Medical Institute · Whitehead Institute for Biomedical Research · +18 more institutions
Abstract
Single-cell (sc)RNA-seq, together with RNA velocity and metabolic labeling, reveals cellular states and transitions at unprecedented resolution. Fully exploiting these data, however, requires kinetic models capable of unveiling governing regulatory functions. Here, we introduce an analytical framework dynamo (https://github.com/aristoteleo/dynamo-release), which infers absolute RNA velocity, reconstructs continuous vector fields that predict cell fates, employs differential geometry to extract underlying regulations, and ultimately predicts optimal reprogramming paths and perturbation outcomes. We highlight dynamo's power to overcome fundamental limitations of conventional splicing-based RNA velocity analyses…
Citation impact
- FWCI
- 38.37
- Percentile
- 100%
- References
- 110
Authors
22- XQXiaojie QiuCorresponding
Howard Hughes Medical Institute, Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology
- YZYan Zhang
University of Pittsburgh
- JDJorge D. Martin-Rufino
Broad Institute, Boston Children's Hospital, Harvard University, Dana-Farber Cancer Institute
- CWChen Weng
Boston Children's Hospital, Howard Hughes Medical Institute, Harvard University, Dana-Farber Cancer Institute, Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology
- SHShayan Hosseinzadeh
University of California, Berkeley
Topics & keywords
- Biology
- Transcriptome
- Vector (molecular biology)
- Computational biology
- Single-cell analysis
- Genetics
- Cell
- Gene expression