De novo analysis for cryo-electron tomography.
This GitHub repository have two branches (git checkout
Python 3 transition completed and changes for being compatible with Scipion. Now PySeg has been ugraded to run Ubunutu 22.04 LTS.
A description of the requirements, auxiliary software, installation and functionality testing is available on docs/manual/manual.pdf file.
You may want to build a docker container to run Pyseg. First, you have build docker image in Dockerfile:
docker build . -t pyseg:latest
Then you can run a terminal on image by:
docker run -it pyseg:latest bash
In this terminal, you can work like in any other Linux terminal having acces to the whole Pyseg funcitionality.
If you just want to run a specific script then (replace the <> placeholders accordingly, a typical location for the /mnt
):
docker run --rm -it -v <data-directory-in-host-machine>:<mount-directory-in-container> pyseg:latest <command> <options>
For the available commands look at USAGE.
In docs/tutorials/synth_sumb/synth_sumb.pdf there is a tutorial for de novo analysis of membrane proteins using self-generated synthetic data, it is strongly recomended to complete this tutorial before starting with your experimental data.
If you have found a bug or have an issue with the software, please open an issue here.
Licensed under the Apache License, Version 2.0 (see LICENSE file)
Template-free particle picking and unsupervised classification (PySeg):
[1] Martinez-Sanchez et al. "Template-free detection and classification of heterogeneous membrane-bound complexes in cryo-electron tomograms" Nature Methods (2020) doi:10.1038/s41592-019-0687-1
Membrane segmentation (TomoSegMemTV):
[2] Martinez-Sanchez et al. "Robust membrane detection based on tensor voting for electron tomography" J Struct Biol (2014) https://doi.org/10.1016/j.jsb.2014.02.015
Statistical spatial analysis (PyOrg):
[3] Martinez-Sanchez, Lucic & Baumeister. "Statistical spatial analysis for cryo-electron tomography" Comput Methods Programs Biomed (2022) https://doi.org/10.1016/j.cmpb.2022.106693