Dataset Information

TrackNTrace: A simple and extendable open-source framework for developing single-molecule localization and tracking algorithms.

ABSTRACT: Super-resolution localization microscopy and single particle tracking are important tools for fluorescence microscopy. Both rely on detecting, and tracking, a large number of fluorescent markers using increasingly sophisticated computer algorithms. However, this rise in complexity makes it difficult to fine-tune parameters and detect inconsistencies, improve existing routines, or develop new approaches founded on established principles. We present an open-source MATLAB framework for single molecule localization, tracking and super-resolution applications. The purpose of this software is to facilitate the development, distribution, and comparison of methods in the community by providing a unique, easily extendable plugin-based system and combining it with a novel visualization system. This graphical interface incorporates possibilities for quick inspection of localization and tracking results, giving direct feedback of the quality achieved with the chosen algorithms and parameter values, as well as possible sources for errors. This is of great importance in practical applications and even more so when developing new techniques. The plugin system greatly simplifies the development of new methods as well as adapting and tailoring routines towards any research problem's individual requirements. We demonstrate its high speed and accuracy with plugins implementing state-of-the-art algorithms and show two biological applications.

SUBMITTER: Stein SC

PROVIDER: S-EPMC5122847 | biostudies-other | 2016 Nov

REPOSITORIES: biostudies-other

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TrackNTrace: A simple and extendable open-source framework for developing single-molecule localization and tracking algorithms.

Stein Simon Christoph SC Thiart Jan J

Scientific reports 20161125

Super-resolution localization microscopy and single particle tracking are important tools for fluorescence microscopy. Both rely on detecting, and tracking, a large number of fluorescent markers using increasingly sophisticated computer algorithms. However, this rise in complexity makes it difficult to fine-tune parameters and detect inconsistencies, improve existing routines, or develop new approaches founded on established principles. We present an open-source MATLAB framework for single molec ...[more]

PMID: 27885259

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Project description:Single-molecule Förster Resonance Energy Transfer (smFRET) allows probing intermolecular interactions and conformational changes in biomacromolecules, and represents an invaluable tool for studying cellular processes at the molecular scale. smFRET experiments can detect the distance between two fluorescent labels (donor and acceptor) in the 3-10 nm range. In the commonly employed confocal geometry, molecules are free to diffuse in solution. When a molecule traverses the excitation volume, it emits a burst of photons, which can be detected by single-photon avalanche diode (SPAD) detectors. The intensities of donor and acceptor fluorescence can then be related to the distance between the two fluorophores. While recent years have seen a growing number of contributions proposing improvements or new techniques in smFRET data analysis, rarely have those publications been accompanied by software implementation. In particular, despite the widespread application of smFRET, no complete software package for smFRET burst analysis is freely available to date. In this paper, we introduce FRETBursts, an open source software for analysis of freely-diffusing smFRET data. FRETBursts allows executing all the fundamental steps of smFRET bursts analysis using state-of-the-art as well as novel techniques, while providing an open, robust and well-documented implementation. Therefore, FRETBursts represents an ideal platform for comparison and development of new methods in burst analysis. We employ modern software engineering principles in order to minimize bugs and facilitate long-term maintainability. Furthermore, we place a strong focus on reproducibility by relying on Jupyter notebooks for FRETBursts execution. Notebooks are executable documents capturing all the steps of the analysis (including data files, input parameters, and results) and can be easily shared to replicate complete smFRET analyzes. Notebooks allow beginners to execute complex workflows and advanced users to customize the analysis for their own needs. By bundling analysis description, code and results in a single document, FRETBursts allows to seamless share analysis workflows and results, encourages reproducibility and facilitates collaboration among researchers in the single-molecule community.

Dataset Information

TrackNTrace: A simple and extendable open-source framework for developing single-molecule localization and tracking algorithms.

Publications

TrackNTrace: A simple and extendable open-source framework for developing single-molecule localization and tracking algorithms.

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