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Cell-connectivity-guided trajectory inference from single-cell data
MOTIVATION: Single-cell RNA-sequencing enables cell-level investigation of cell differentiation, which can be modelled using trajectory inference methods. While tremendous effort has been put into designing these methods, inferring accurate trajectories automatically remains difficult. Therefore, th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474950/ https://www.ncbi.nlm.nih.gov/pubmed/37624916 http://dx.doi.org/10.1093/bioinformatics/btad515 |
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author | Smolander, Johannes Junttila, Sini Elo, Laura L |
author_facet | Smolander, Johannes Junttila, Sini Elo, Laura L |
author_sort | Smolander, Johannes |
collection | PubMed |
description | MOTIVATION: Single-cell RNA-sequencing enables cell-level investigation of cell differentiation, which can be modelled using trajectory inference methods. While tremendous effort has been put into designing these methods, inferring accurate trajectories automatically remains difficult. Therefore, the standard approach involves testing different trajectory inference methods and picking the trajectory giving the most biologically sensible model. As the default parameters are often suboptimal, their tuning requires methodological expertise. RESULTS: We introduce Totem, an open-source, easy-to-use R package designed to facilitate inference of tree-shaped trajectories from single-cell data. Totem generates a large number of clustering results, estimates their topologies as minimum spanning trees, and uses them to measure the connectivity of the cells. Besides automatic selection of an appropriate trajectory, cell connectivity enables to visually pinpoint branching points and milestones relevant to the trajectory. Furthermore, testing different trajectories with Totem is fast, easy, and does not require in-depth methodological knowledge. AVAILABILITY AND IMPLEMENTATION: Totem is available as an R package at https://github.com/elolab/Totem. |
format | Online Article Text |
id | pubmed-10474950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104749502023-09-03 Cell-connectivity-guided trajectory inference from single-cell data Smolander, Johannes Junttila, Sini Elo, Laura L Bioinformatics Original Paper MOTIVATION: Single-cell RNA-sequencing enables cell-level investigation of cell differentiation, which can be modelled using trajectory inference methods. While tremendous effort has been put into designing these methods, inferring accurate trajectories automatically remains difficult. Therefore, the standard approach involves testing different trajectory inference methods and picking the trajectory giving the most biologically sensible model. As the default parameters are often suboptimal, their tuning requires methodological expertise. RESULTS: We introduce Totem, an open-source, easy-to-use R package designed to facilitate inference of tree-shaped trajectories from single-cell data. Totem generates a large number of clustering results, estimates their topologies as minimum spanning trees, and uses them to measure the connectivity of the cells. Besides automatic selection of an appropriate trajectory, cell connectivity enables to visually pinpoint branching points and milestones relevant to the trajectory. Furthermore, testing different trajectories with Totem is fast, easy, and does not require in-depth methodological knowledge. AVAILABILITY AND IMPLEMENTATION: Totem is available as an R package at https://github.com/elolab/Totem. Oxford University Press 2023-08-25 /pmc/articles/PMC10474950/ /pubmed/37624916 http://dx.doi.org/10.1093/bioinformatics/btad515 Text en © The Author(s) 2023. 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 | Original Paper Smolander, Johannes Junttila, Sini Elo, Laura L Cell-connectivity-guided trajectory inference from single-cell data |
title | Cell-connectivity-guided trajectory inference from single-cell data |
title_full | Cell-connectivity-guided trajectory inference from single-cell data |
title_fullStr | Cell-connectivity-guided trajectory inference from single-cell data |
title_full_unstemmed | Cell-connectivity-guided trajectory inference from single-cell data |
title_short | Cell-connectivity-guided trajectory inference from single-cell data |
title_sort | cell-connectivity-guided trajectory inference from single-cell data |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474950/ https://www.ncbi.nlm.nih.gov/pubmed/37624916 http://dx.doi.org/10.1093/bioinformatics/btad515 |
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