scFates：一个用于从单细胞数据中进行高级拟时和分支分析的可扩展 Python 包。
scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data.
机构信息
Department of Neuroimmunology, Center for Brain Research, Medical University Vienna, 1090 Vienna, Austria.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.
出版信息
Bioinformatics. 2023 Jan 1;39(1). doi: 10.1093/bioinformatics/btac746.
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.
摘要
scFates 提供了广泛的工具集，用于分析包含树学习、特征关联测试、分支差异表达的动态轨迹，并侧重于分叉处的细胞偏向和命运分裂。它旨在完全集成到 scanpy 生态系统中，用于对来自各种模态（例如 RNA 和 ATAC）的单细胞数据的轨迹进行无缝分析。
可用性和实现
scFates 作为开源软件发布，根据 BSD 3-Clause“新”许可证，可从 Python 包索引 https://pypi.org/project/scFates/ 获得。源代码可在 GitHub 上获得 https://github.com/LouisFaure/scFates/。在已发表数据集上的代码再现和教程可在 GitHub 上获得 https://github.com/LouisFaure/scFates_notebooks。
补充信息
补充数据可在生物信息学在线获得。
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