title: Visualizing cellular imaging data using PhenoPlot.
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.
authors.affiliation: Dynamical Cell Systems, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK.
authors.forename: Heba Z
authors.initials: HZ
authors.lastname: Sailem
authors.affiliation: Dynamical Cell Systems, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK.
authors.forename: Julia E
authors.initials: JE
authors.lastname: Sero
authors.affiliation: Dynamical Cell Systems, Division of Cancer Biology, Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Bakal
mesh_terms: D001943:Breast Neoplasms / Q000648:ultrastructure*; D045744:Cell Line, Tumor; D002477:Cells / Q000648:ultrastructure*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012984:Software