Interpreting Image-based Profiles using Similarity Clustering and Single-Cell Visualization

被引:6
|
作者
Garcia-Fossa, Fernanda [1 ,2 ]
Cruz, Mario Costa [1 ]
Haghighi, Marzieh [1 ]
de Jesus, Marcelo Bispo [2 ]
Singh, Shantanu [1 ]
Carpenter, Anne E. [1 ]
Cimini, Beth A. [1 ]
机构
[1] Broad Inst Harvard & MIT, Imaging Platform, Cambridge, MA 02142 USA
[2] Univ Estadual Campinas, Inst Biol, Dept Biochem & Tissue Biol, Campinas, SP, Brazil
来源
CURRENT PROTOCOLS | 2023年 / 3卷 / 03期
基金
美国国家卫生研究院; 巴西圣保罗研究基金会;
关键词
high-dimensional data; image-based profiling; Morpheus; morphological analysis; profiling; single-cell visualization;
D O I
10.1002/cpz1.713
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Image-based profiling quantitatively assesses the effects of perturbations on cells by capturing a breadth of changes via microscopy. Here, we provide two complementary protocols to help explore and interpret data from image-based profiling experiments. In the first protocol, we examine the similarity among perturbed cell samples using data from compounds that cluster by their mechanisms of action. The protocol includes steps to examine feature-driving differences between samples and to visualize correlations between features and treatments to create interpretable heatmaps using the open-source web tool Morpheus. In the second protocol, we show how to interactively explore images together with the numerical data, and we provide scripts to create visualizations of representative single cells and image sites to understand how changes in features are reflected in the images. Together, these two tutorials help researchers interpret image-based data to speed up research. (c) 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.Basic Protocol 1: Exploratory analysis of profile similarities and driving featuresBasic Protocol 2: Image and single-cell visualization following profile interpretation
引用
收藏
页数:21
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