SPTAnalyser

Processing of single particle tracking data:

• MSD-based extraction of diffusion coefficients and diffusion types
• Time resolved analysis of MSD-based analysis
• Transition counting between different diffusion modes
• Hidden Markov modeling with ermine^[1]

The pipeline is compatible with PALMTracer^[2], rapidSTORM^[3], ThunderSTORM^[4] and swift^[5]

To install the package run

cd C:\path\to\SPTAnalyser
conda create --name SPTAnalyser python=3.8
conda activate SPTAnalyser
conda install pip pywin32
pip install jupyterlab
python -m pip install pyErmine
pip install SPTAnalyser-XXX-py3-none-any.whl
pip install jupyter_contrib_nbextensions
jupyter notebook

The analysis is described in great detail in the Manual_Tracking_Routine.pdf. Give the analysis a try with the test files in the dataset folder, including localization files from ThunderSTORM, tracked files from swift, and SPTAnalyser trackAnalysis output. More single-particle tracking data can be found at https://www.ebi.ac.uk/biostudies/studies/S-BSST712.

Contributors

Johanna Rahm, Sebastian Malkusch, Marie-Lena Harwardt, Marina Dietz, Claudia Catapano, Alexander Niedrig

Literature

[1] https://github.com/SMLMS/pyErmine
[2] PALMTracer download
[3] S. Wolter, A. Löschberger, T. Holm, S. Aufmkolk, M.-C. Dabauvalle, S. van de Linde, M. Sauer, 2012, Nature Methods, 9, 1040-1041, DOI: 10.1038/nmeth.2224
[4] M. Ovesny, P. Krizek, J. Borkovec, Z. Svindrych, G. M. Hagen, 2014, Bioinformatics, 30, 2389-2390, DOI: 10.1093/bioinformatics/btu202
[5] M. Endesfelder, C. Schießl, B. Turkowyd, T. Lechner, U. Endesfelder, Manuscript in Prep.; swift download

Citation

Please cite our paper when using SPTAnalyser for your research.
J. V. Rahm, S. Malkusch, U. Endesfelder, M. S. Dietz, M. Heilemann, Front. Comput. Sci., 12 November 2021, https://doi.org/10.3389/fcomp.2021.757653