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CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data
Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell’s progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581332/ https://www.ncbi.nlm.nih.gov/pubmed/36275810 http://dx.doi.org/10.3389/fmed.2022.919345 |
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author | Hadj Abed, Louisa Tak, Tamar Cosgrove, Jason Perié, Leïla |
author_facet | Hadj Abed, Louisa Tak, Tamar Cosgrove, Jason Perié, Leïla |
author_sort | Hadj Abed, Louisa |
collection | PubMed |
description | Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell’s progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data. |
format | Online Article Text |
id | pubmed-9581332 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95813322022-10-20 CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data Hadj Abed, Louisa Tak, Tamar Cosgrove, Jason Perié, Leïla Front Med (Lausanne) Medicine Single-cell lineage tracing permits the labeling of individual cells with a heritable marker to follow the fate of each cell’s progeny. Over the last twenty years, several single-cell lineage tracing methods have emerged, enabling major discoveries in developmental biology, oncology and gene therapies. Analytical tools are needed to draw meaningful conclusions from lineage tracing measurements, which are characterized by high variability, sparsity and technical noise. However, the single cell lineage tracing field lacks versatile and easy-to-use tools for standardized and reproducible analyses, in particular tools accessible to biologists. Here we present CellDestiny, a RShiny app and associated web application developed for experimentalists without coding skills to perform visualization and analysis of single cell lineage-tracing datasets through a graphical user interface. We demonstrate the functionality of CellDestiny through the analysis of (i) lentiviral barcoding datasets of murine hematopoietic progenitors; (ii) published integration site data from Wiskott-Aldrich Symdrome patients undergoing gene-therapy treatment; and (iii) simultaneous barcoding and transcriptomic analysis of murine hematopoietic progenitor differentiation in vitro. In summary, CellDestiny is an easy-to-use and versatile toolkit that enables biologists to visualize and analyze single-cell lineage tracing data. Frontiers Media S.A. 2022-10-05 /pmc/articles/PMC9581332/ /pubmed/36275810 http://dx.doi.org/10.3389/fmed.2022.919345 Text en Copyright © 2022 Hadj Abed, Tak, Cosgrove and Perié. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Hadj Abed, Louisa Tak, Tamar Cosgrove, Jason Perié, Leïla CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title | CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title_full | CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title_fullStr | CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title_full_unstemmed | CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title_short | CellDestiny: A RShiny application for the visualization and analysis of single-cell lineage tracing data |
title_sort | celldestiny: a rshiny application for the visualization and analysis of single-cell lineage tracing data |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581332/ https://www.ncbi.nlm.nih.gov/pubmed/36275810 http://dx.doi.org/10.3389/fmed.2022.919345 |
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