Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour

With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that enable researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that allow flexible, interactive and intuitive analysis from raw images to analysed data are lacking for many experimental use-cases. Notably, integrated software solutions for analysis of complex 3D and live cell images are sorely needed. To address this, we present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative multidimensional image analysis accessible for non-specialists. We describe the application of Cecelia to several immunologically relevant scenarios and the development of an unbiased approach to distinguish dynamic cell behaviours from live imaging data. Cecelia is available as a software package with a Shiny app interface ( https://github.com/schienstockd/cecelia ). We envision that this framework and its approaches will be of broad use for biological researchers.