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UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference
The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model v...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633790/ https://www.ncbi.nlm.nih.gov/pubmed/36329018 http://dx.doi.org/10.1038/s41467-022-34188-7 |
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author | Gao, Mingze Qiao, Chen Huang, Yuanhua |
author_facet | Gao, Mingze Qiao, Chen Huang, Yuanhua |
author_sort | Gao, Mingze |
collection | PubMed |
description | The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches. |
format | Online Article Text |
id | pubmed-9633790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96337902022-11-05 UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference Gao, Mingze Qiao, Chen Huang, Yuanhua Nat Commun Article The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches. Nature Publishing Group UK 2022-11-03 /pmc/articles/PMC9633790/ /pubmed/36329018 http://dx.doi.org/10.1038/s41467-022-34188-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Gao, Mingze Qiao, Chen Huang, Yuanhua UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title | UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title_full | UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title_fullStr | UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title_full_unstemmed | UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title_short | UniTVelo: temporally unified RNA velocity reinforces single-cell trajectory inference |
title_sort | unitvelo: temporally unified rna velocity reinforces single-cell trajectory inference |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633790/ https://www.ncbi.nlm.nih.gov/pubmed/36329018 http://dx.doi.org/10.1038/s41467-022-34188-7 |
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