Pyto

General description

Detection and analysis of macromolecular complexes and proteins in 3D cryo-electron images (tomograms). While it was developed for neuronal synapses, it is applicable to other biological systems.

Specific tasks

• The main purpose is the detection and analysis of pleomorphic membrane-bound molecular complexes cryo-electron tomograms.

• Correlate images obtained from light microscopy and different modes of electron microscopy (transmission and scanning electron microscopy, focused ion beam microscopy). A part of this code is used in 3DCT package for correlative microscopy, which provides GUI.

• Spatial distribution analysis of particles (such as complexes)

• Preprocessing membrane-bound particles (complexes) for subtomogram averaging.

• Mapping complexes to their exact position and angular orientation for visualization.

• Provides tools that assist general processing of cryo-electron tomograms (frame alignment, 3D reconstruction).

Dependencies:

The current version is written in Python 3. The code was originally written in Python 2 and subsequently converted to Python 3.6. While most of the code is currently compatible with Python 2.7, this will not be enforced in future.

Major dependencies of this package are:

• NumPy
• SciPy
• Pandas
• future

In addition, some parts depend on:

• Matplotlib
• Sklearn
• Skimage
• Statsmodels
• SymPy: Currently needed only for development
• PySeg: Needed only if Pyseg colocalization processing is followed by Pyto. Make sure Pyto comes before PySeg in PYTHONPATH because PySeg contains an older version of Pyto

• PyTorch: Needed only for neural net classification

Installation

Put this directory to your PYTHONPATH

Documentation

Please start from Overview.

Release history

• 1.11.2 (21.5.2026, svn r2285)
  • Updated colocalization task example
• 1.11.1 (17.1.2026, svn r2263)
  • Added membrane / boundary normal vectors
  • Improved preprocessing for averaging and handling pixel size in Layers.rebin()
• 1.11.0 (27.10.2025, svn r2239)
  • Added colocalization example
  • Improved colocalization code and docs for pattern generation and reading star files
• 1.10.3 (7.05.2025, svn 2202)
  • Added AI tether classification code and example
• 1.10.2 (30.03.2025, svn r2181)
  • Added mapping particle code and example
  • Fixed some depreciation related issues for python 3.12
  • Docs improvements, small fixes
• 1.10.1 (07.01.2025, svn r2155)
  • Added preprocessing for subtomo averaging example
  • Put back sources for manuals
• 1.10.0 (18.12.2024, svn r2140)
  • Added preprocessing for subtomo averaging
  • Improved particle handling (MultiParticlesets)
  • The above are needed for the Tether averaging project
• 1.9.2 (19.03.2024, svn r2102)
  • Added projection methods for colocalization analysis
  • Added particle extraction from tomos
  • Removed dependence on imp module to make pyseg compatible with Python 3.12+
• 1.9.1 (18.10.2023, svn r2024)
  • Noted future module dependency
  • Removed references to numpy.testing.Tester (removd from numpy 1.24)
• 1.9 (7.12.2021, svn r1824)
  • Added colocalization analysis (developed for Martinez-Sanchez et al 2021 "Trans-synaptic assemblies link synaptic vesicles and neuroreceptors" DOI: 10.1126/sciadv.abe6204)
  • Added functionality to extract additional features of segments
• 1.8 (31.10.2021, svn r1771)
  • Added classes for basic geometrical shapes (Plane, Parallelogram)
  • Added bin_crop script
  • Improved analysis: Groups to/from Pandas, correlation analysis and graphs
• 1.7
  • Added presynaptic example
  • Improved docs
  • Small improvements
• 1.6
  • The first public release.

License

Copyright (C) 2010 Vladan Lucic

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.

Citing

Please consider citing us if you use Pyto:

• For general use, segmentation and analysis: Lučić V, Fernández-Busnadiego R, Laugks U and Baumeister W, 2016. Hierarchical detection and analysis of macromolecular complexes in cryo-electron tomograms using Pyto software. J Struct Biol. 196(3):503-514. http://dx.doi.org/10.1016/j.jsb.2016.10.004.

• For colocalization analysis, please cite: Daniel H. Orozco-Borunda, Antonio Martinez-Sanchez, Vladan Lucic, 2025, Spatial organization of assemblies of protein complexes by colocalization analysis BIORXIV/2025/684783.

• For 3D to 2D correlation, please cite: Arnold, J., J. Mahamid, V. Lucic, A. d. Marco, J.-J. Fernandez, Laugks, H.-A. Mayer, Tobias, W. Baumeister, and J. Plitzko, 2016. Site-specific cryo-focused ion beam sample preparation guided by 3-dimensional correlative microscopy. Biophysical Journal 110:860-869. http://dx.doi.org/10.1016/j.bpj.2015.10.053.

• For all other correlative work: Fukuda, Y., N. Schrod, M. Schaffer, L. R. Feng, W. Baumeister, and V. Lucic, 2014. Coordinate transformation based cryo-correlative methods for electron tomography and focused ion beam milling. Ultramicroscopy 143:15– 23. http://dx.doi.org/10.1016/j.ultramic.2013.11.008.

Thank you.

Author

Vladan Lucic (vladan@biochem.mpg.de), Max Planck Institute for Biochemistry