Abstract
scFates provides an extensive toolset for the analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a focus on cell biasing and fate splits at the level of bifurcations. It is meant to be fully integrated into the scanpy ecosystem for seamless analysis of trajectories from single-cell data of various modalities (e.g. RNA and ATAC).
Cite
CITATION STYLE
Faure, L., Soldatov, R., Kharchenko, P. V., & Adameyko, I. (2023). scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data. Bioinformatics, 39(1). https://doi.org/10.1093/bioinformatics/btac746
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.