Package: pyFRET
What is pyFRET?pyFRET is a python package for analysis of data from single-molecule fluorescence (smFRET) experiments using confocal laser microscopy.
pyFRET provides methods for:parsing filesburst selection and denoisingFRET Efficiency calculationdata visualisationGaussian fits of smFRET histogramspyFRET supports analysis of data collected using both continuous (FRET) and alternating excitation (ALEX).pyFRET was written by Rebecca R. Murphy (email:rebeccaroisin@gmail.com) and is licenced under an OSI-compliant BSD licence.
Please see LICENSE.txt for the text of the license.How is pyFRET structured?pyFRET is one module. It contains two submodules:pyFRET for continuous excitation datapyALEX for alternating excitation dataHow do I use pyFRET?pyFRET is on the Python Package Index (PyPI). From your terminal, it can be installed using “pip install pyFRET”.
To use the library functions in your code, you can use “from pyFRET import pyFRET” and “from pyFRET import pyALEX”.Detailed installation instructions can be found in the onlinetutorialDetailed usage instructions can be found in thepyFRETandpyALEXreferences, in the onlinetutorialor in the docs folder.Example code, including configuration files, for complete data analysis using pyFRET can be found in the bin folder.Specifically, what does pyFRET do?Currently, for simple FRET data, pyFRET supports:file parsing for .csv and binary (.dat) filesparsing lists of photon counts into data objectsAll Photons Burst Search (APBS)Dual Channel Burst Search (DCBS)AND, SUM and OR thresholdingcalculating proximity ratio (including optional gamma-factor correction)building and plotting proximity ratio histograms, including export as .csv files3D plots of smFRET datascatterplots for smFRET dataGaussian fitting using a single gaussian peak, including export of fits as .csv filesRecurrence Analysis of Single Particles, as implemented in Hoffmann et al. Phys Chem Chem Phys. 2011 13(5):1857-1871.For ALEX data, pyFRET supports:file parsing for .csv and binary filesparsing lists of photon counts into data objectsAll Photons Burst Search (APBS)Dual Channel Burst Search (DCBS)calculation of the Proximity Ratio and Stoichiometry (including optional gamma-factor correction)event selection using calculated stoichiometrybuilding and plotting proximity ratio histograms, including export as .csv filesconstruction of scatter plot with projections of E and SGaussian fitting using a single gaussian peak, including export of fits as .csv filesCurrently, pyFRETdoes notimplement:probability distribution analysis to denoise fluorescence burstsGaussian fitting of multiple populationssupport for multi-parameter fluorescence detection.pyFRET currently does not have a parser for data collected using PicoQuant instrumentation.These are all important features, which it would be very useful to add. If you would like to see these features added, email me (rebeccaroisin@gmail.com), or contribute a patch.How do I get in touch?pyFRET is hosted onBitbucketin a public coderepository. It’s justhereIf you find a bug, go to the issuetrackerand add an issue, including a description of the problem you have found.You can also create an issue if there is a feature that you would like to see added to the pyFRET library.If you would like to contribute a patch or feature to the code, please clone the repository, create a new local branch and make your changes locally. Run the unit tests to check that you didn’t break anything and then push back to the main branch. If you don’t feel confident doing that, add an issue or email me and we can fix it together.