Seidel software for FRET-nanoscopy analysis

functionality

1. reading photon streams from picoquant .ptu files and transforming them into xy-lifetime images
2. Bayesian framework to optimally determine the number and location of emitters in an image snapshot
3. Forming individual emitters into FRET pairs and calculating FRET parameters
4. Bayesian framework for fitting 1D histograms with non-centered Chi and Gaussian distributions.
5. Molecular assembly particle averaging based on coarse alignment and Prokrustes analysis

System requirements

Software consists of python code with a c++ backend. The latter is responsible for computation intensive tasks of reading ptu files, creating images and performing gaussian fits. Python software was build on python 3.7 using libraries available in the anaconda standard cluster of libraries. c++ code was compiled into a .pyd file that requires windows 10 standard dll's to run.

• python 3.7
• anaconda libraries
• windows 10
  Software was tested by several users under these settings, no non-standard hardware is required.

installation guide

1. clone the /FRC/Code into a local directory
2. include the path to your local copy of /FRC/Code in your PYTHONPATH
3. Seidel depends on the lmfit scikit-image numpy scipy matplotlib tiffile packages included in the metapackage anaconda. The package rmsd must be downloaded separately using pip install rmsd In case of any problems, please contact [email protected]. Installation time should be less than a minute.

Demo notebook & example data

For a step-by-step instruction on how to use Seidel on FRET nanoscopy data, refer to this notebook. The notebook shows expected results for comparison. Run-time is ~1 second per ptu file. A small dataset of ptu files is provided for running the ptu reading and spot detection software. A larger sample is not provided due to size limitations, but can be obtained by reasonable request from the authors. Additionally, a fully analysed dataset is provided in compressed form. This data may be unzipped and read by the template notebook to perform all subsequent analyses and fits. Similarly, to reproduce published results obtained using Seidel, please request the relevent dataset and accompanying analysis notebook.

dedication

The Seidel software is dedicated to Prof. C.A.M. Seidel from the Institute of Molecular Physcial Chemistry at the HHU university, the PhD supervisor of the author.