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Protein velocity and acceleration from single-cell multiomics experiments

The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages e...

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Detalles Bibliográficos
Autores principales: Gorin, Gennady, Svensson, Valentine, Pachter, Lior
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029606/
https://www.ncbi.nlm.nih.gov/pubmed/32070398
http://dx.doi.org/10.1186/s13059-020-1945-3
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author Gorin, Gennady
Svensson, Valentine
Pachter, Lior
author_facet Gorin, Gennady
Svensson, Valentine
Pachter, Lior
author_sort Gorin, Gennady
collection PubMed
description The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package.
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spelling pubmed-70296062020-02-25 Protein velocity and acceleration from single-cell multiomics experiments Gorin, Gennady Svensson, Valentine Pachter, Lior Genome Biol Short Report The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package. BioMed Central 2020-02-18 /pmc/articles/PMC7029606/ /pubmed/32070398 http://dx.doi.org/10.1186/s13059-020-1945-3 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
Gorin, Gennady
Svensson, Valentine
Pachter, Lior
Protein velocity and acceleration from single-cell multiomics experiments
title Protein velocity and acceleration from single-cell multiomics experiments
title_full Protein velocity and acceleration from single-cell multiomics experiments
title_fullStr Protein velocity and acceleration from single-cell multiomics experiments
title_full_unstemmed Protein velocity and acceleration from single-cell multiomics experiments
title_short Protein velocity and acceleration from single-cell multiomics experiments
title_sort protein velocity and acceleration from single-cell multiomics experiments
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029606/
https://www.ncbi.nlm.nih.gov/pubmed/32070398
http://dx.doi.org/10.1186/s13059-020-1945-3
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