ShinySOM: graphical SOM-based analysis of single-cell cytometry data

SUMMARY: ShinySOM offers a user-friendly interface for reproducible, high-throughput analysis of high-dimensional flow and mass cytometry data guided by self-organizing maps. The software implements a FlowSOM-style workflow, with improvements in performance, visualizations and data dissection possib...

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Detalles Bibliográficos
Autores principales: Kratochvíl, Miroslav, Bednárek, David, Sieger, Tomáš, Fišer, Karel, Vondrášek, Jiří
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214046/
https://www.ncbi.nlm.nih.gov/pubmed/32049322
http://dx.doi.org/10.1093/bioinformatics/btaa091
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author Kratochvíl, Miroslav
Bednárek, David
Sieger, Tomáš
Fišer, Karel
Vondrášek, Jiří
author_facet Kratochvíl, Miroslav
Bednárek, David
Sieger, Tomáš
Fišer, Karel
Vondrášek, Jiří
author_sort Kratochvíl, Miroslav
collection PubMed
description SUMMARY: ShinySOM offers a user-friendly interface for reproducible, high-throughput analysis of high-dimensional flow and mass cytometry data guided by self-organizing maps. The software implements a FlowSOM-style workflow, with improvements in performance, visualizations and data dissection possibilities. The outputs of the analysis include precise statistical information about the dissected samples, and R-compatible metadata useful for the batch processing of large sample volumes. AVAILABILITY AND IMPLEMENTATION: ShinySOM is free and open-source, available online at gitlab.com/exaexa/ShinySOM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-72140462020-05-15 ShinySOM: graphical SOM-based analysis of single-cell cytometry data Kratochvíl, Miroslav Bednárek, David Sieger, Tomáš Fišer, Karel Vondrášek, Jiří Bioinformatics Applications Notes SUMMARY: ShinySOM offers a user-friendly interface for reproducible, high-throughput analysis of high-dimensional flow and mass cytometry data guided by self-organizing maps. The software implements a FlowSOM-style workflow, with improvements in performance, visualizations and data dissection possibilities. The outputs of the analysis include precise statistical information about the dissected samples, and R-compatible metadata useful for the batch processing of large sample volumes. AVAILABILITY AND IMPLEMENTATION: ShinySOM is free and open-source, available online at gitlab.com/exaexa/ShinySOM. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-05-15 2020-02-12 /pmc/articles/PMC7214046/ /pubmed/32049322 http://dx.doi.org/10.1093/bioinformatics/btaa091 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://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 Notes
Kratochvíl, Miroslav
Bednárek, David
Sieger, Tomáš
Fišer, Karel
Vondrášek, Jiří
ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title_full ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title_fullStr ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title_full_unstemmed ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title_short ShinySOM: graphical SOM-based analysis of single-cell cytometry data
title_sort shinysom: graphical som-based analysis of single-cell cytometry data
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214046/
https://www.ncbi.nlm.nih.gov/pubmed/32049322
http://dx.doi.org/10.1093/bioinformatics/btaa091
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