Visualizing cellular imaging data using PhenoPlot.
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Embargo End Date
ICR Authors
Authors
Sailem, HZ
Sero, JE
Bakal, C
Sero, JE
Bakal, C
Document Type
Journal Article
Date
2015-01-08
Date Accepted
2014-11-11
Abstract
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.
Citation
Nature communications, 2015, 6 pp. 5825 - ?
Source Title
Publisher
NATURE PUBLISHING GROUP
ISSN
2041-1723
eISSN
2041-1723
Collections
Research Team
Dynamical Cell Systems