Alice Schoenauer Sebag1, Sandra Plancade2, Céline Raulet-Tomkiewicz3, Robert Barouki3, Jean-Philippe Vert4, Thomas Walter4. 1. MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France. 2. MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France. 3. MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France. 4. MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, Fontainebleau, Institut Curie, Paris, INSERM U900, Paris, Université Paris Descartes, Paris, INSERM UMR-S 1124, Paris, Agro ParisTech, Paris and Mathématiques et Informatique Appliquées, INRA, Jouy-en-Josas, France.
Abstract
MOTIVATION: Motility is a fundamental cellular attribute, which plays a major part in processes ranging from embryonic development to metastasis. Traditionally, single cell motility is often studied by live cell imaging. Yet, such studies were so far limited to low throughput. To systematically study cell motility at a large scale, we need robust methods to quantify cell trajectories in live cell imaging data. RESULTS: The primary contribution of this article is to present Motility study Integrated Workflow (MotIW), a generic workflow for the study of single cell motility in high-throughput time-lapse screening data. It is composed of cell tracking, cell trajectory mapping to an original feature space and hit detection according to a new statistical procedure. We show that this workflow is scalable and demonstrates its power by application to simulated data, as well as large-scale live cell imaging data. This application enables the identification of an ontology of cell motility patterns in a fully unsupervised manner. AVAILABILITY AND IMPLEMENTATION: Python code and examples are available online (http://cbio.ensmp.fr/∼aschoenauer/motiw.html)
MOTIVATION: Motility is a fundamental cellular attribute, which plays a major part in processes ranging from embryonic development to metastasis. Traditionally, single cell motility is often studied by live cell imaging. Yet, such studies were so far limited to low throughput. To systematically study cell motility at a large scale, we need robust methods to quantify cell trajectories in live cell imaging data. RESULTS: The primary contribution of this article is to present Motility study Integrated Workflow (MotIW), a generic workflow for the study of single cell motility in high-throughput time-lapse screening data. It is composed of cell tracking, cell trajectory mapping to an original feature space and hit detection according to a new statistical procedure. We show that this workflow is scalable and demonstrates its power by application to simulated data, as well as large-scale live cell imaging data. This application enables the identification of an ontology of cell motility patterns in a fully unsupervised manner. AVAILABILITY AND IMPLEMENTATION: Python code and examples are available online (http://cbio.ensmp.fr/∼aschoenauer/motiw.html)
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