About PyCorrFit
In current biomedical research, fluorescence correlation spectroscopy (FCS) is applied to characterize molecular dynamic processes in vitro and in living cells. Commercial FCS setups only permit data analysis that is limited to a specific instrument by the use of in-house file formats or a finite number of implemented correlation model functions. PyCorrFit is a general-purpose FCS evaluation software that, amongst other formats, supports the established Zeiss ConfoCor3 ~.fcs file format. PyCorrFit comes with several built-in model functions, covering a wide range of applications in standard confocal FCS. In addition, it contains equations dealing with different excitation geometries like total internal reflection (TIR).
Supported operating systems
Windows 7 and higher
Linux (Debian-based)
Any other operating system with a Python 3.6 installation (via pip)
Supported filetypes
ALV correlators (~.ASC)
Correlator.com (Flex) correlators (~.SIN)
Zeiss ConfoCor3 (~.fcs)
PicoQuant (~.pt3) as implemented by Dominic Waithe (https://github.com/dwaithe/FCS_point_correlator)
PyCorrFit (~.csv)
PyCorrFit session (~.pcfs)
Fitting
Pre-defined model functions (confocal FCS, TIR-FCS, triplet blinking, multiple components)
Import of user-defined model functions
Global fitting across multiple model functions or data sets
Least squares fit using Levenberg-Marquard, Simplex, and more
Weighted fitting with standard deviation
Tools and Features
Averaging of curves
Background correction
Batch processing
Overlay tool to identify outliers
Fast simulation of model parameter behavior
Session management
High quality plot export using LaTeX (bitmap or vector graphics)
How to cite
Müller, P., Schwille, P., and Weidemann, T. PyCorrFit - generic data evaluation for fluorescence correlation spectroscopy. Bioinformatics 30(17):2532-2533 (2014). doi:10.1093/bioinformatics/btu328