STracking: a free and open-source Python library for particle tracking and analysis

Abstract Summary Analysis of intra- and extracellular dynamic like vesicles transport involves particle tracking algorithms. The design of a particle tracking pipeline is a routine but tedious task. Therefore, particle dynamics analysis is often performed by combining several pieces of software (fil...

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Bibliographic Details
Published in:Bioinformatics Vol. 38; no. 14; pp. 3671 - 3673
Main Authors: Prigent, Sylvain, Valades-Cruz, Cesar Augusto, Leconte, Ludovic, Salamero, Jean, Kervrann, Charles
Format: Journal Article
Language:English
Published: England Oxford University Press 11.07.2022
Oxford University Press (OUP)
Subjects:
Algorithms
Cell Behavior
Cellular Biology
Computer Science
Gene Library
Libraries
Life Sciences
Signal and Image Processing
Software
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
Online Access:Get full text
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Summary:Abstract Summary Analysis of intra- and extracellular dynamic like vesicles transport involves particle tracking algorithms. The design of a particle tracking pipeline is a routine but tedious task. Therefore, particle dynamics analysis is often performed by combining several pieces of software (filtering, detection, tracking, etc.) requiring many manual operations, and thus leading to poorly reproducible results. Given the new segmentation tools based on deep learning, modularity and interoperability between software have become essential in particle tracking algorithms. A good synergy between a particle detector and a tracker is of paramount importance. In addition, a user-friendly interface to control the quality of estimated trajectories is necessary. To address these issues, we developed STracking, a Python library that allows combining algorithms into standardized particle tracking pipelines. Availability and implementation STracking is available as a Python library using ‘pip install’ and the source code is publicly available on GitHub (https://github.com/sylvainprigent/stracking). A graphical interface is available using two napari plugins: napari-stracking and napari-tracks-reader. These napari plugins can be installed via the napari plugins menu or using ‘pip install’. The napari plugin source codes are available on GitHub (https://github.com/sylvainprigent/napari-tracks-reader, https://github.com/sylvainprigent/napari-stracking). Supplementary information Supplementary data are available at Bioinformatics online.
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btac365