pyFRET: A Python Library for Single Molecule Fluorescence Data Analysis

TL;DR

pyFRET is an open source Python library that simplifies and standardizes the analysis of single-molecule FRET data, supporting various experimental setups and encouraging community contributions.

Contribution

This work introduces pyFRET, the first comprehensive open source Python package for smFRET data analysis, with extensive documentation and community support.

Findings

Provides complete analysis pipeline for smFRET data

Supports both continuous and ALEX excitation data

Accessible via PyPI with open source licensing

Abstract

Single molecule F\"orster resonance energy transfer (smFRET) is a powerful experimental technique for studying the properties of individual biological molecules in solution. However, as adoption of smFRET techniques becomes more widespread, the lack of available software, whether open source or commercial, for data analysis, is becoming a significant issue. Here, we present pyFRET, an open source Python package for the analysis of data from single-molecule fluorescence experiments from freely diffusing biomolecules. The package provides methods for the complete analysis of a smFRET dataset, from burst selection and denoising, through data visualisation and model fitting. We provide support for both continuous excitation and alternating laser excitation (ALEX) data analysis. pyFRET is available as a package downloadable from the Python Package Index (PyPI) under the open source three-clause BSD licence, together with links to extensive documentation and tutorials, including example usage and test data. Additional documentation including tutorials is hosted independently on ReadTheDocs. The code is available from the free hosting site Bitbucket. Through distribution of this software, we hope to lower the barrier for the adoption of smFRET experiments by other research groups and we encourage others to contribute modules for specific analysis needs.