TRamWAy: mapping physical properties of individual biomolecule random motion in large-scale single-particle tracking experiments

François Laurent (1, 2) , Hippolyte Verdier (1, 3, 4) , Maxime Duval (1) , Alexander Serov (1) , Christian L Vestergaard (1) , Jean-Baptiste Masson (1)

1 Décision et processus Bayesiens - Decision and Bayesian Computation
2 Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB
3 Sanofi [Vitry-sur-Seine]
4 UPCité - Université Paris Cité

Motivation: Single-molecule localization microscopy allows studying the dynamics of biomolecules in cells and resolving the biophysical properties of the molecules and their environment underlying cellular function. With the continuously growing amount of data produced by individual experiments, the computational cost of quantifying these properties is increasingly becoming the bottleneck of single-molecule analysis. Mining these data requires an integrated and efficient analysis toolbox. Results: We introduce TRamWAy, a modular Python library that features: (i) a conservative tracking procedure for localization data, (ii) a range of sampling techniques for meshing the spatio-temporal support of the data, (iii) computationally efficient solvers for inverse models, with the option of plugging in user-defined functions and (iv) a collection of analysis tools and a simple web-based interface. Availability and implementation: TRamWAy is a Python library and can be installed with pip and conda. The source code is available at https://github.com/DecBayComp/TRamWAy.

Domaines: Bio-informatique [q-bio.QM]

François Laurent, Hippolyte Verdier, Maxime Duval, Alexander Serov, Christian L Vestergaard, et al.. TRamWAy: mapping physical properties of individual biomolecule random motion in large-scale single-particle tracking experiments. Bioinformatics, 2022, 38 (11), pp.3149-3150. ⟨10.1093/bioinformatics/btac291⟩. ⟨pasteur-03695448⟩