Skip to main content

This is a library to performe phasor analysis in microscopy images

Project description

Logo

PhasorPy: A Python library for phasor analysis

Time-resolved (FLIM) and hyperspectral imaging (HSI) have become paramount in biomedical science. The power of the combination between traditional imaging and spectroscopy opens the possibility to address information inaccessible before. For bioimaging analysis of these data, the Phasor plots are a tool revolutionizing the field because of their straightforward approach. Thus it is becoming a key player in democratizing access to FLIM and HSI

PhasorPy library is based on SimFCS, a software developed by Enrico Gratton at the Laboratory for Fluorescence Dynamic, University of California, Irvine. PhasorPy is a library for FLIM and HSI data analysis using the phasor approach. The phasor approach was developed as model free method and relies on the fourier transform properties.

Documentation

doc

Phasor Analysis

Considering an hyperspectral image, the fluorescence spectra at each pixel can be transformed in phasor coordinates (G (λ)) and (S (λ)). I(λ) represent the intensity at every wavelength (channel), n is the number of the harmonic and λ i the initial wavelength. The, x and y coordinates are plotted in the spectral phasor plot.

The position for every pixel in the spectral phasor plot can be defined by the phase angle and the modulus (M) given the coordinates G and S.

The angular position in the spectral phasor plot relates to the center of mass of the emission spectrum and the modulus depends on the spectrum’s full width at the half maximum (FWHM). For instance, if the spectrum is broad its location should be close to the center. Otherwise, if there is a red shift in the spectrum, its location will move counterclockwise toward increasing angle from position (1, 0). Spectral phasors have the same vector properties as lifetime phasors. A detailed description of the spectral phasor plot properties can be found in Malacrida et al. 1.

Installation

  pip install PhasorPy
  conda install PhasorPy

Authors

License

MIT

Contributing

Contributions are always very well welcome. The PhasorPy library intends to create an open-source and collaborative community between spectroscopy and fluorescence microscopy users with the same functionalities as SimFCS but accessible and self-sustainable in the long term as other Python libraries and communities.

References

[1] Malacrida, L., Gratton, E. & Jameson, D. M. Model-free methods to study membrane environmental probes: A comparison of the spectral phasor and generalized polarization approaches. Methods Appl. Fluoresc. 3, 047001 (2015).

Used and maintain By

This project is used and maintain:

  • Advance Bioimaging Unit at Institt Pasteur Montevideo and Universidad de la República

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PhasorPy-1.0.2.tar.gz (9.9 kB view hashes)

Uploaded Source

Built Distribution

PhasorPy-1.0.2-py3-none-any.whl (11.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page