Welcome to PyPhotoMol, a python-package to analyse mass photometry data.
- Data Import: Import HDF5 (.h5) and csv mass photometry data files, generated by Refeyn instruments (https://refeyn.com).
- Histogram Analysis: Create histograms of mass or contrast distributions
- Peak Detection: Automated peak finding in histograms using peak height, distance and prominence
- Mass-Contrast Conversion: Convert between mass and contrast with calibration parameters
- Gaussian Fitting: Fit multiple Gaussians to the histogram data
- Comprehensive Logging: Track all operations with logbooks
Install PyPhotoMol with pip:
pip install pyphotomolfrom pyphotomol import PyPhotoMol
# Create a new analysis instance
model = PyPhotoMol()
# Import data from an HDF5 file
model.import_file('data.h5')
# Create a histogram and detect peaks
model.create_histogram(use_masses=True, window=[0, 1000], bin_width=10)
model.guess_peaks(min_height=10, min_distance=4, prominence=4)
# Fit Gaussian models to detected peaks
model.fit_histogram(
peaks_guess=model.peaks_guess,
mean_tolerance=200,
std_tolerance=300
)
# Create and view results
model.create_fit_table()
print(model.fit_table)PyPhotoMol is derived from PhotoMol, an online tool presented in the following publication:
Niebling, Stephan, et al. "Biophysical Screening Pipeline for Cryo-EM Grid Preparation of Membrane Proteins." Frontiers in Molecular Biosciences 9 (2022): 903148.