CellRank 2: unified fate mapping in multiview single-cell data
Helmholtz Zentrum München · Technical University of Munich · +4 more institutions
Abstract
Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories; however, trajectory inference does not incorporate valuable time point information or utilize additional modalities, whereas methods that address these different data views cannot be combined or do not scale. Here we present CellRank 2, a versatile and scalable framework to study cellular fate using multiview single-cell data of up to millions of cells in a unified fashion. CellRank 2 consistently recovers terminal states and fate probabilities across data modalities in human hematopoiesis and endodermal development. Our framework also…
Citation impact
- FWCI
- 39.04
- Percentile
- 100%
- References
- 106
Authors
5- PWPhilipp WeilerCorresponding
Helmholtz Zentrum München, Technical University of Munich
- MLMarius Lange
Helmholtz Zentrum München, ETH Zurich, Technical University of Munich
- MKMichal Klein
Apple (Israel), Helmholtz Zentrum München
- DPDana Pe’er
Memorial Sloan Kettering Cancer Center, Howard Hughes Medical Institute
- FJFabian J. Theis
Helmholtz Zentrum München, Technical University of Munich
Topics & keywords
- Cell fate determination
- Computer science
- Computational biology
- Scalability
- Inference
- Fate mapping
- Endoderm
- Transcriptome
Funding
- JHJoachim Herz Stiftung
- ECEuropean CommissionAward: 101054957
- BFBundesministerium für Bildung und ForschungAwards: 031A537C, 031A533A, 031A535A, 031A537A, 031A538A, 031A537D, 031A534A, 031A532B, 031A533B, 031A537B
- GNGerman Network for Bioinformatics InfrastructureAwards: 031A533A, 031A534A, 031A538A, 031A537D, 031A537A, 031A535A, 031A532B, 031A537B, 031A533B, 031A537C
- HZHelmholtz Zentrum München