Abstract
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.
Funder
Academy of Finland
Sigrid Juséliuksen Säätiö
Syöpäjärjestöt
Åbo Akademi
HORIZON EUROPE Framework Programme
Fundação Calouste Gulbenkian
H2020 European Research Council
INCEPTION project
Fondation Bettencourt Schueller
France BioImaging
European Molecular Biology Organization
Chan Zuckerberg Initiative
LS4FUTURE Associated Laboratory
Stiftelsen för Åbo Akademi
Publisher
Public Library of Science (PLoS)