PhasorPy#

PhasorPy is an open-source Python library for the analysis of luminescence lifetime and hyperspectral images using the phasor approach.

The phasor approach represents time-resolved and spectral signals as phasor coordinates (normalized Fourier coefficients at harmonic frequencies) for intuitive visualization and analysis.

PhasorPy enables reproducible phasor-based fluorescence lifetime imaging (FLIM) and hyperspectral imaging (HSI) workflows in scientific Python. It provides tools to read microscopy data in many file formats and to calculate, calibrate, filter, visualize, and interconvert phasor coordinates, lifetimes, and signals. Phasor coordinates can be exported to standard formats and analyzed through cursor-based region-of-interest selection, cluster detection, multi-component unmixing, FRET efficiency and concentration estimation.

Introduction to PhasorPy

Introduction to PhasorPy

Introduction to PhasorPy
Geometric interpretation of lifetimes

Geometric interpretation of lifetimes

Geometric interpretation of lifetimes
File input/output

File input/output

File input/output
Förster resonance energy transfer

Förster resonance energy transfer

Förster resonance energy transfer
Interactive applications

Interactive applications

Interactive applications
Multi-component fit

Multi-component fit

Multi-component fit
Absolute NADH concentration

Absolute NADH concentration

Absolute NADH concentration
All tutorials...

All tutorials...

All tutorials...

Documentation#

The PhasorPy documentation thoroughly documents all aspects of the library, including:

Other versions: latest development, all

Resources#

News#

Events#

The PhasorPy project is presented at the following events:

Publications#

Using PhasorPy

  1. Schuty B, Garcia MJ, Khuon S, Malacrida L. Phasor analysis of RGB camera data enables fluorescence microscopy unmixing and brightfield segmentation in a commercial microscope. Sens Bio-Sens Res. 52: 101014 (2026)

  2. Prieto D, Rehermann MI, Fabbiani G, Vitar M, Trujillo-Cenoz O, Falco MV, Cuparo M, Trigo FF, et al. A filopodia-based dendritic mechanosensory compartment in CSF-contacting neurons. bioRxiv (2026)

  3. Halbers LP, Brennan CK, Scipioni L, Tedeschi G, Torrey ZR, Parag-Sharma K, Labra B, Gohlke C, et al. Expanded applications of bioluminescence microscopy with phasor analysis. Cell Rep Methods. 6(4): 101344 (2026)

  4. Fuller EB, Cole KH, Halbers LP, Chan CET, Ng KK, Scipioni L, Gohlke C, Digman MA, et al. Bioluminescent probes for multiplexed RNA imaging. J Am Chem Soc. 148(11): 11521-11530 (2026)

  5. Pannunzio B, Cespedes P, Diaz M, Ali D, Rial A, Malacrida L. High-throughput single-cell spectroscopy using phasor analysis of spectral flow cytometry. bioRxiv (2026)

  6. Zhao W, Samimi K, Skala MC, Datta R. FLIM playground: an interactive, end-to-end graphical user interface for analyzing single cells with fluorescence lifetime imaging microscopy. bioRxiv (2025)

Mentioning PhasorPy

  1. Harkhoe R, Ferrari G, Dmitriev RI, Kuhl M. Luminescence lifetime imaging: Key concepts and advances in the image acquisition, processing, and analysis pipeline. ACS Meas Sci Au. acsmeasuresciau.5c00209 (2026)

  2. Georgakoudi I, Skala MC, Quinn KP, Stringari C, Sorrells JE, Heikal AA, Li LZ, Xu HN, et al. Consensus guidelines for cellular label-free optical metabolic imaging: ensuring accuracy and reproducibility in metabolic profiling. J Biomed Opt. 30(S2): S23901 (2025)

  3. Wetzker C, Zoccoler ML, Iarovenko S, Okafornta CW, Nobst A, Hartmann H, Muller-Reichert T, Haase R, et al. A fluorescence lifetime separation approach for FLIM live-cell imaging. J Microscopy. 301(1): 91-106 (2025)

  4. Michalet X. AlliGator: open source fluorescence lifetime imaging analysis in G. bioRxiv (2025)

  5. Kapsiani S, Laubli NF, Ward EN, Shehata M, Kaminski CF, Kaminski Schierle GS. FLIMPA: a versatile software for fluorescence lifetime imaging microscopy phasor analysis. Anal Chem. 97(22): 11382-11387 (2025)

  6. Vallmitjana A, Torrado B, Durkin AF, Dvornikov A, Rajil N, Ranjit S, Balu M. GSLab: open-source platform for advanced phasor analysis in fluorescence microscopy. Bioinformatics. 41(4): btaf162 (2025)

  7. Weber F, Iskrak S, Ragaller F, Schlegel J, Plochberger B, Sezgin E, Andronico LA. VISION - an open-source software for automated multi-dimensional image analysis of cellular biophysics. J Cell Sci. 137(20): jcs262166 (2024)

Cite#

Please cite doi: 10.5281/zenodo.13862586 if PhasorPy contributes to research that leads to a publication.

Contact#

PhasorPy is a community-maintained project.

Contributions in the form of bug reports, bug fixes, feature implementations, documentation, datasets, and enhancement proposals are welcome.

Report issues and ask questions about PhasorPy on the GitHub issue tracker.

Alternatively, contact the PhasorPy developers directly.