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ggCyto: next generation open-source visualization software for cytometry

MOTIVATION: Open source software for computational cytometry has gained in popularity over the past few years. Efforts such as FlowCAP, the Lyoplate and Euroflow projects have highlighted the importance of efforts to standardize both experimental and computational aspects of cytometry data analysis....

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Detalles Bibliográficos
Autores principales: Van, Phu, Jiang, Wenxin, Gottardo, Raphael, Finak, Greg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223365/
https://www.ncbi.nlm.nih.gov/pubmed/29868771
http://dx.doi.org/10.1093/bioinformatics/bty441
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author Van, Phu
Jiang, Wenxin
Gottardo, Raphael
Finak, Greg
author_facet Van, Phu
Jiang, Wenxin
Gottardo, Raphael
Finak, Greg
author_sort Van, Phu
collection PubMed
description MOTIVATION: Open source software for computational cytometry has gained in popularity over the past few years. Efforts such as FlowCAP, the Lyoplate and Euroflow projects have highlighted the importance of efforts to standardize both experimental and computational aspects of cytometry data analysis. The R/BioConductor platform hosts the largest collection of open source cytometry software covering all aspects of data analysis and providing infrastructure to represent and analyze cytometry data with all relevant experimental, gating and cell population annotations enabling fully reproducible data analysis. Data visualization frameworks to support this infrastructure have lagged behind. RESULTS: ggCyto is a new open-source BioConductor software package for cytometry data visualization built on ggplot2 that enables ggplot-like functionality with the core BioConductor flow cytometry data structures. Amongst its features are the ability to transform data and axes on-the-fly using cytometry-specific transformations, plot faceting by experimental meta-data variables and partial matching of channel, marker and cell populations names to the contents of the BioConductor cytometry data structures. We demonstrate the salient features of the package using publicly available cytometry data with complete reproducible examples in a Supplementary Material. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/devel/bioc/html/ggcyto.html SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-62233652018-11-14 ggCyto: next generation open-source visualization software for cytometry Van, Phu Jiang, Wenxin Gottardo, Raphael Finak, Greg Bioinformatics Applications Notes MOTIVATION: Open source software for computational cytometry has gained in popularity over the past few years. Efforts such as FlowCAP, the Lyoplate and Euroflow projects have highlighted the importance of efforts to standardize both experimental and computational aspects of cytometry data analysis. The R/BioConductor platform hosts the largest collection of open source cytometry software covering all aspects of data analysis and providing infrastructure to represent and analyze cytometry data with all relevant experimental, gating and cell population annotations enabling fully reproducible data analysis. Data visualization frameworks to support this infrastructure have lagged behind. RESULTS: ggCyto is a new open-source BioConductor software package for cytometry data visualization built on ggplot2 that enables ggplot-like functionality with the core BioConductor flow cytometry data structures. Amongst its features are the ability to transform data and axes on-the-fly using cytometry-specific transformations, plot faceting by experimental meta-data variables and partial matching of channel, marker and cell populations names to the contents of the BioConductor cytometry data structures. We demonstrate the salient features of the package using publicly available cytometry data with complete reproducible examples in a Supplementary Material. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/devel/bioc/html/ggcyto.html SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-11-15 2018-06-01 /pmc/articles/PMC6223365/ /pubmed/29868771 http://dx.doi.org/10.1093/bioinformatics/bty441 Text en © The Author(s) 2018. 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
Van, Phu
Jiang, Wenxin
Gottardo, Raphael
Finak, Greg
ggCyto: next generation open-source visualization software for cytometry
title ggCyto: next generation open-source visualization software for cytometry
title_full ggCyto: next generation open-source visualization software for cytometry
title_fullStr ggCyto: next generation open-source visualization software for cytometry
title_full_unstemmed ggCyto: next generation open-source visualization software for cytometry
title_short ggCyto: next generation open-source visualization software for cytometry
title_sort ggcyto: next generation open-source visualization software for cytometry
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223365/
https://www.ncbi.nlm.nih.gov/pubmed/29868771
http://dx.doi.org/10.1093/bioinformatics/bty441
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