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scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data.

Authors :
Faure L
Soldatov R
Kharchenko PV
Adameyko I
Source :
Bioinformatics (Oxford, England) [Bioinformatics] 2023 Jan 01; Vol. 39 (1).
Publication Year :
2023

Abstract

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).<br />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.<br />Supplementary Information: Supplementary data are available at Bioinformatics online.<br /> (© The Author(s) 2022. Published by Oxford University Press.)

Subjects

Subjects :
Ecosystem
Software

Details

Language :
English
ISSN :
1367-4811
Volume :
39
Issue :
1
Database :
MEDLINE
Journal :
Bioinformatics (Oxford, England)
Publication Type :
Academic Journal
Accession number :
36394263
Full Text :
https://doi.org/10.1093/bioinformatics/btac746