Tools for working with single-molecule localization data.
Project description
biteen-utilities
A repository for common coding tasks in the Biteen Lab.
Methods:
biteen_io.py:
Reading, writing, and converting between different file types.
- convert .nd2 to .tif
- convert .nd2 to .npy
- extract ROIs from cellpose .npy into 2d numpy array
- convert cellpose .npy to .mat (SMALL-LABS format)
- convert SMALL-LABS output (*_fits.mat, *_guesses.mat) to pandas DataFrame
- convert SMALL-LABS output (*_fits.mat, *_guesses.mat) to .csv
- convert pandas DataFrame to SMALL-LABS format .mat
- convert SMALL-LABS output to Spot-On format
- convert pandas DataFrame to Spot-On format
biteen_pandas.py:
Working with tabular data stored in pandas DataFrames.
- calculate individual step data from localizations
- filter localization data by number of localizations in each track
- calculate median step size for each track
biteen_plots.py
Plotting single-molecule data.
- Plot localizations overlayed on image data, e.g. phase contrast
- Plot trajectories overlayed on image data, e.g. phase contrast
Future
- dpsp related format conversions
- drift correction with RCC
- using napari
- MSD
- using NOBIAS output
- heatmaps
- rotation to align with cell axes
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