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<p>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 (<a href="https://github.com/schienstockd/cecelia">https://github.com/schienstockd/cecelia</a>). We envision that this framework and its approaches will be of broad use for biological researchers.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月24日

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  • Dominik Schienstock,
  • Jyh Liang Hor,
  • Sapna Devi,
  • Scott N. Mueller

摘要

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.