Unveiling the Power of High-Dimensional Cytometry Data with cyCONDOR

High-dimensional cytometry (HDC) is a powerful tool for studying single-cells phenotypes in a complex system. Although in recent years the combination of technological developments and affordability have made HDC broadly available, these technological advances were not paired with the adequate development of analytical methods to take full advantage of the data generated. While several platforms and bioinformatics tools are currently available for the analysis of HDC data, they are either web-hosted with limited scalability or designed for expert computational biologists, making them difficult to approach by wet lab scientists. Additionally, the need for end-to-end HDC data analysis tools within a unified ecosystem poses a significant challenge, as researchers must navigate multiple platforms and software packages to complete the analysis. We developed an easy-to-use computational framework (condor) covering not only all of the essential steps of cytometry data analysis but also including an array of downstream functions and tools to expand the biological interpretation of the data. condor’s comprehensive suite of features, including guided pre-processing, clustering, dimensionality reduction, and machine learning algorithms, facilitates the seamless integration of condor into clinically relevant settings, where scalability and disease classification are paramount for the widespread adoption of HDC in clinical practice. Additionally, condor’s advanced analytical features, such as pseudotime analysis and batch integration, provide researchers with the tools to extract deeper insights from their data. We used condor on a variety of data from different tissues and technologies demonstrating its versatility to assist the analysis of high dimensionality data from preprocessing to biological interpretation.

Recommended citation: Charlotte Kroeger, Sophie Mueller, Jacqueline Leidner*, Theresa Kroeber, Stefanie Warnat-Herresthal, Jannis B Spintge, Timo Zajac, Aleksej Frolov, Caterina Carraro, Simone Puccio, Joachim L Schultze, Tal Pecht, Marc D Beyer, Lorenzo Bonaguro*. (2024). "Unveiling the Power of High-Dimensional Cytometry Data with cyCONDOR (2024)"." BioRvix.
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