Cryo-EM Automatic Semantic Segmentation based Particle pickER
A Semantic Segmentation based Particle Picking Algorithm for Single Particle Cryo-Electron Microscopy
https://zenodo.org/badge/latestdoi/231048773
This repository contains the following:
The Labelling Tool is used to generate segmented labels for fresh training of CASSPER. The tool and sample mrc files are given in the sub folder. All the labels used for the study is also provided. The instructions and Demo video for operating the labelling tool is also given in the subfolder.
The mrc files and segmented labels are needed for fresh training. The detailed description is given in the subfolder-Train_and_Predict
The TSaved folder containing the trained weights for different proteins obtained from CASSPER can be found here.
If prediction without training is to be done, the folder TSaved, containing the saved weights, should be added into the respective protein folder in Train_and_Predict folder.
The detailed instructions about labelling, training and prediction are mentioned in the README files of the respective subfolders. Instructions about labelling tool: https://github.com/airis4d/CASSPER/tree/master/Labelling_Tool and Training and prediction:https://github.com/airis4d/CASSPER/tree/master/Train_and_Predict
In Linux, just run setup.sh to set up the virtual environment for CASSPER. In that case, you may skip the following procedure.
CASSPER runs on Python 3.6+. We recommend running it from within a virtual environment.
If you are familiar with virtualenv
, you can use it to create
a virtual environment.
For Python 3.6, create a new environment with your preferred virtualenv wrapper, for example:
- virtualenvwrapper (Bourne-shells)
- virtualfish (fish-shell)
Either follow instructions here or install via
pip
.
$ pip install virtualenv
Then, create a virtualenv
environment by creating a new directory for a Python 3.6 virtualenv environment
$ virtualenv --python=python3.6 cassper
where python3.6
is a valid reference to a Python 3.6 executable.
Activate the environment
$ source cassper/bin/activate
Note: make sure that the environment is activated throughout the installation process.
When you are done, deactivate it using
source deactivate
, or deactivate
depending on your version.
In the project root directory, run the following to install the required packages. Note that this commands installs the packages within the activated virtual environment.
$ pip install -r requirements.txt
Please remember to activate this virtual environment each time you run the codes and run the codes from respective sub-directories itself.
This folder contains Particle stacks ( in .star format) obtained using crYOLO, CASSPER and Gautomatch for four proteins discussed in the paper https://www.nature.com/articles/s42003-021-01721-1. The 2D images used for 3D reconstruction is also marked and shown for all cases in the folder Publication/2D_images