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使用PhenoPlot可视化细胞成像数据。

Visualizing cellular imaging data using PhenoPlot.

作者信息

Sailem Heba Z, Sero Julia E, Bakal Chris

机构信息

Dynamical Cell Systems, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK.

出版信息

Nat Commun. 2015 Jan 8;6:5825. doi: 10.1038/ncomms6825.

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.

摘要

可视化对于数据解读、假设形成以及结果交流至关重要。然而,对于通过高内涵分析生成的图像衍生数据集,用于描述复杂细胞表型的可视化方法却很匮乏,其中复杂细胞表型被表示为特征的高维向量。在此,我们展示了一种可视化工具PhenoPlot,它将定量高内涵成像数据表示为易于解读的符号,并且我们说明了如何使用PhenoPlot来改进对复杂乳腺癌细胞表型的探索和解读。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ba/4354266/e644f753bd3b/ncomms6825-f1.jpg

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