Visualizing cellular imaging data using PhenoPlot

Heba Sailem, Julia Sero, Chris Bakal

Research output: Contribution to journalArticle

23 Citations (Scopus)

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.
Original languageEnglish
Article number5825
JournalNature Communications
Volume6
DOIs
Publication statusPublished - 8 Jan 2015

Keywords

  • computer vision
  • data visualisation
  • High content imaging

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