A1 Refereed original research article in a scientific journal
CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data
Authors: Gómez-de-Mariscal, Estibaliz; Grobe, Hanna; Pylvänäinen, Joanna W.; Xénard, Laura; Henriques, Ricardo; Tinevez, Jean-Yves; Jacquemet, Guillaume
Publisher: PUBLIC LIBRARY SCIENCE
Publishing place: SAN FRANCISCO
Publication year: 2024
Journal: PLoS Biology
Journal name in source: PLOS BIOLOGY
Journal acronym: PLOS BIOL
Article number: e3002740
Volume: 22
Issue: 8
Number of pages: 19
ISSN: 1544-9173
eISSN: 1545-7885
DOI: https://doi.org/10.1371/journal.pbio.3002740
Web address : https://doi.org/10.1371/journal.pbio.3002740
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/457597093
In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches. Here, we introduce CellTracksColab, a platform tailored to simplify the exploration and analysis of cell tracking data. CellTracksColab facilitates the compiling and analysis of results across multiple fields of view, conditions, and repeats, ensuring a holistic dataset overview. CellTracksColab also harnesses the power of high-dimensional data reduction and clustering, enabling researchers to identify distinct behavioral patterns and trends without bias. Finally, CellTracksColab also includes specialized analysis modules enabling spatial analyses (clustering, proximity to specific regions of interest). We demonstrate CellTracksColab capabilities with 3 use cases, including T cells and cancer cell migration, as well as filopodia dynamics. CellTracksColab is available for the broader scientific community at https://github.com/CellMigrationLab/CellTracksColab.Exploring large amounts of cell tracking data remains a challenge. This study presents CellTracksColab, a platform that provides a transformative solution for cell tracking analysis, combining cutting-edge computational methods with a user-friendly interface.
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Funding information in the publication:
This study was supported by the Research Council of Finland (338537 to GJ, https:// www.aka.fi/en/), the Sigrid Jus\u00E9lius Foundation (to GJ, https://www.sigridjuselius.fi/en/), the Cancer Society of Finland (Sy\u00F6p\u00E4j\u00E4rjest\u00F6t; to GJ, https:// www.cancersociety.fi/), and the Solutions for Health strategic funding to \u00C5bo Akademi University (to GJ, https://www.abo.fi/en/solutions-for-health/). This research was supported by the InFLAMES Flagship Programme of the Academy of Finland (decision numbers: 337530, 337531, 357910, and 357911, https://www.aka.fi/en/). EGM and RH received funding from the European Union through the Horizon Europe program (AI4LIFE project with grant agreement 101057970-AI4LIFE, and RTSuperES project with grant agreement 101099654-RTSuperES to RH, https://research-and-innovation. ec.europa.eu/funding/funding-opportunities/ funding-programmes-and-open-calls/horizoneurope_en). EGM and RH also acknowledge the support of the Gulbenkian Foundation (Funda\u00E7\u00E3o Calouste Gulbenkian, https://gulbenkian.pt/en/) and the European Research Council (ERC) under the European Union\u2019s Horizon 2020 research and innovation program (grant agreement No. 101001332 to RH, https://erc.europa.eu/ homepage). LX received funding from the INCEPTION project (PIA/ANR-16-CONV-0005, https://anr.fr/) and is a student from the FIRE PhD program funded by the Bettencourt Schueller Foundation (https://www.fondationbs.org/en) and the EURIP graduate program (ANR-17-EURE-0012, https://www.learningplanetinstitute.org/en/ eurip-graduate-school/). This study was also supported by France BioImaging (Investissement d\u2019Avenir; ANR-10-INBS-04, J.-Y. T., LX, https:// france-bioimaging.org/). This work was also supported by the European Molecular Biology Organization (EMBO, https://www.embo.org/) Installation Grant (EMBO-2020-IG-4734 to RH), the EMBO Postdoctoral Fellowship (EMBO ALTF 174-2022 to EGM), the Chan Zuckerberg Initiative (https://chanzuckerberg.com/) Visual Proteomics Grant (vpi-0000000044 with DOI:10.37921/ 743590vtudfp to RH). RH also acknowledges the support of LS4FUTURE Associated Laboratory (LA/ P/0087/2020, https://www.ls4future.pt/). The open access publication fees were funded by the G\u00F6sta Branders research fund, \u00C5bo Akademi Research Foundation (G\u00F6sta Branders forskningsfond, Stiftelsen f\u00F6r \u00C5bo Akademi, https://stiftelsenabo.fi/ en/home/). While the European Union funded this study, the views and opinions expressed are those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible. None of the funders listed above were involved in the design and execution of this study. We thank Hellyeh Hamidi for providing feedback on this manuscript. The Cell Imaging and Cytometry Core facility (Turku Bioscience, University of Turku, \u00C5bo Akademi University, and Biocenter Finland) and Turku Bioimaging are acknowledged for services, instrumentation, and expertise.
