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Gene-level alignment of single-cell trajectories
Paper Details
Published: 2024/12/16
Journal: Nature Methods
Pages: 1-14
Paper Links
HTMLThis paper presents Genes2Genes, a new Bayesian information-theoretic alignment framework for single-cell pseudotime trajectories. It demonstrates the utility of trajectory alignment for disease cell-state analysis and in vitro vs. in vivo comparative studies for organoid protocol refinement. Genes2Genes was developed as an open source Python package available at: https://github.com/Teichlab/Genes2Genes.
Authors
C. Suo
A.M. Cujba
D. Muraro
E. Dann
K. Polanski
A.S. Steemers
W. Lee
A.J. Oliver
J.E. Park