CryoPARES Documentation

CryoPARES is a software package for assigning poses to 2D cryo-electron microscopy (cryo-EM) particle images using supervised deep learning.

The key idea is to train a neural network on a high-quality reference reconstruction, and then reuse this trained model to rapidly estimate particle poses in other, similar datasets.

User Guide

API Reference

Additional Resources

Quick Start

Installation

conda create -n cryopares python=3.12
conda activate cryopares
pip install git+https://github.com/rsanchezgarc/cryoPARES.git

Training

ulimit -n 65536  # Increase file descriptor limit

cryopares_train \
    --symmetry C1 \
    --particles_star_fname /path/to/aligned_particles.star \
    --train_save_dir /path/to/output \
    --n_epochs 20

Inference

cryopares_infer \
    --particles_star_fname /path/to/new_particles.star \
    --checkpoint_dir /path/to/output/version_0 \
    --results_dir /path/to/results

Indices and tables