TY - JOUR T1 - The Image Data Explorer: interactive exploration of image-derived data JF - bioRxiv DO - 10.1101/2022.04.27.489647 SP - 2022.04.27.489647 AU - Coralie Muller AU - Beatriz Serrano-Solano AU - Yi Sun AU - Christian Tischer AU - Jean-Karim Hériché Y1 - 2022/01/01 UR - http://biorxiv.org/content/early/2022/08/22/2022.04.27.489647.abstract N2 - Many bioimage analysis projects produce quantitative descriptors of regions of interest in images. Associating these descriptors with visual characteristics of the objects they describe is a key step in understanding the data at hand. However, as many bioimage data and their analysis workflows are moving to the cloud, addressing interactive data exploration in remote environments has become a pressing issue. To address it, we developed the Image Data Explorer (IDE) as a web application that integrates interactive linked visualization of images and derived data points with exploratory data analysis methods, annotation, classification and feature selection functionalities. The IDE is written in R using the shiny framework. It can be easily deployed on a remote server or on a local computer. The IDE is available at https://git.embl.de/heriche/image-data-explorer and a cloud deployment is accessible at https://shiny-portal.embl.de/shinyapps/app/01_image-data-explorer.Competing Interest StatementThe authors have declared no competing interest. ER -