Visualizing cellular imaging data using PhenoPlot

Visualization is essential for data interpretation, hypothesis formulation and communication of results. However, there is a paucity of visualization methods for image-derived data sets generated by high-content analysis in which complex cellular phenotypes are described as high-dimensional vectors...

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Detalles Bibliográficos
Autores principales: Sailem, Heba Z., Sero, Julia E., Bakal, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354266/
https://www.ncbi.nlm.nih.gov/pubmed/25569359
http://dx.doi.org/10.1038/ncomms6825
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author Sailem, Heba Z.
Sero, Julia E.
Bakal, Chris
author_facet Sailem, Heba Z.
Sero, Julia E.
Bakal, Chris
author_sort Sailem, Heba Z.
collection PubMed
description Visualization is essential for data interpretation, hypothesis formulation and communication of results. However, there is a paucity of visualization methods for image-derived data sets generated by high-content analysis in which complex cellular phenotypes are described as high-dimensional vectors of features. Here we present a visualization tool, PhenoPlot, which represents quantitative high-content imaging data as easily interpretable glyphs, and we illustrate how PhenoPlot can be used to improve the exploration and interpretation of complex breast cancer cell phenotypes.
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spelling pubmed-43542662015-03-20 Visualizing cellular imaging data using PhenoPlot Sailem, Heba Z. Sero, Julia E. Bakal, Chris Nat Commun Article Visualization is essential for data interpretation, hypothesis formulation and communication of results. However, there is a paucity of visualization methods for image-derived data sets generated by high-content analysis in which complex cellular phenotypes are described as high-dimensional vectors of features. Here we present a visualization tool, PhenoPlot, which represents quantitative high-content imaging data as easily interpretable glyphs, and we illustrate how PhenoPlot can be used to improve the exploration and interpretation of complex breast cancer cell phenotypes. Nature Pub. Group 2015-01-08 /pmc/articles/PMC4354266/ /pubmed/25569359 http://dx.doi.org/10.1038/ncomms6825 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Sailem, Heba Z.
Sero, Julia E.
Bakal, Chris
Visualizing cellular imaging data using PhenoPlot
title Visualizing cellular imaging data using PhenoPlot
title_full Visualizing cellular imaging data using PhenoPlot
title_fullStr Visualizing cellular imaging data using PhenoPlot
title_full_unstemmed Visualizing cellular imaging data using PhenoPlot
title_short Visualizing cellular imaging data using PhenoPlot
title_sort visualizing cellular imaging data using phenoplot
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354266/
https://www.ncbi.nlm.nih.gov/pubmed/25569359
http://dx.doi.org/10.1038/ncomms6825
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