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Updated: Aug 20, 2025
AMEBaS: Automatic Midline Extraction and Background Subtraction of Ratiometric Fluorescence Time-Lapses of Polarized Single Cells
Published on: June 23, 2023
scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data
Louis Faure1, Ruslan Soldatov2, Peter V Kharchenko2,3
1Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, 1090 Vienna, Austria.
Summary:
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).
Availability And Implementation:
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 and tutorials on published datasets are available on GitHub at https://github.com/LouisFaure/scFates_notebooks.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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