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scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data
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 sca...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805561/ https://www.ncbi.nlm.nih.gov/pubmed/36394263 http://dx.doi.org/10.1093/bioinformatics/btac746 |
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author | Faure, Louis Soldatov, Ruslan Kharchenko, Peter V Adameyko, Igor |
author_facet | Faure, Louis Soldatov, Ruslan Kharchenko, Peter V Adameyko, Igor |
author_sort | Faure, Louis |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9805561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98055612023-01-03 scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data Faure, Louis Soldatov, Ruslan Kharchenko, Peter V Adameyko, Igor Bioinformatics Applications Note 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. Oxford University Press 2022-11-17 /pmc/articles/PMC9805561/ /pubmed/36394263 http://dx.doi.org/10.1093/bioinformatics/btac746 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Faure, Louis Soldatov, Ruslan Kharchenko, Peter V Adameyko, Igor scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title | scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title_full | scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title_fullStr | scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title_full_unstemmed | scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title_short | scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
title_sort | scfates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805561/ https://www.ncbi.nlm.nih.gov/pubmed/36394263 http://dx.doi.org/10.1093/bioinformatics/btac746 |
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