TY - JOUR
T1 - CellTracksColab is a platform that enables compilation, analysis, and exploration of cell tracking data
AU - Gómez-de-Mariscal, Estibaliz
AU - Grobe, Hanna
AU - Pylvänäinen, Joanna W
AU - Xénard, Laura
AU - Henriques, Ricardo
AU - Tinevez, Jean-Yves
AU - Jacquemet, Guillaume
N1 - Copyright: © 2024 Gómez-de-Mariscal et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2024/8/8
Y1 - 2024/8/8
N2 - 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.
AB - 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.
KW - Cell Tracking/methods
KW - Humans
KW - Cell Movement
KW - Software
KW - Animals
KW - Image Processing, Computer-Assisted/methods
KW - Pseudopodia/physiology
KW - T-Lymphocytes
KW - Mice
U2 - 10.1371/journal.pbio.3002740
DO - 10.1371/journal.pbio.3002740
M3 - Article
C2 - 39116189
SN - 1544-9173
VL - 22
JO - PLoS Biology
JF - PLoS Biology
IS - 8
M1 - e3002740
ER -