scFates provides an extensive toolset for 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 scanpy ecosystem for seamless analysis of trajectories from single cell data of various modalities (e.g. RNA, ATAC).scFates is released as open-source software under the BSD 3-Clause ”New” License and is available from the Python Package Index at https://pypi.org/project/scFates/. The source code is available on Github at https://github.com/LouisFaure/scFates/. Code reproduction, tutorials on publised datasets are available on Github at https://github.com/LouisFaure/scFates_notebooks.A supplementary document with a complete explanation of the underlying statistics, benchmark figures and showing examples of analysis, is available at Bioinformatics online.
btac746
