Last updated
Last updated
This job is a wrapper for , a deep learning model trained to perform masking-like and sharpening-like postprocessing on cryo-EM maps [1].
Structura Biotechnology Inc. and CryoSPARC do not license nor distribute DeepEMhancer binaries. Please ensure you have your own copy of DeepEMhancer licensed and installed under the terms of its .
For the following instructions, do not use the conda command or environment that is installed by CryoSPARC. This installation is destroyed and recreated with CryoSPARC updates, so new environments created by it will be erased and any changes made to it may break other CryoSPARC jobs.
DeepEMhancer depends on other python packages outside of what CryoSPARC provides. In order to install DeepEMhancer using a conda environment, you must use a conda environment manager and a conda environment that is separate from the CryoSPARC conda/python installation, and use that environment to install dependencies.
Install deepEMhancer following one of the methods described in the deepEMhancer repository at .
Important considerations for Master/Worker or Cluster installations:
The path to the conda installation on the machine hosting cryosparc_master must exactly match the path on machines hosting cryosparc_worker. This may be achieved by creating the conda environment in a shared directory that is mounted under the same path on the CryoSPARC master and all workers.
The conda installation directory must be accessible by the CryoSPARC Linux user account with the required permissions for executing the deepemhancer script.
With deepEMhancer installed and its conda environment active in the current shell, run
which deepemhancer
to find the full path to the deepEMhancer script. It should be similar to this:
/home/cryosparcuser/miniforge3/envs/deepEMhancer_env/bin/deepemhancer
Instead of miniforge3, the conda environment manager may have been installed in a differently named directory, like anaconda3 or miniconda3, depending on which conda environment manager you chose to install. Use the applicable directory name when specifying the Path to deepEMhancer executable job parameter or inside the (optional) wrapper shell script.
When running the CryoSPARC wrapper, input this as the value for the ‘Path to deepEMhancer executable’ parameter.
The CryoSPARC and deepEMhancer environments and dependencies may conflict. As a workaround, you may need to wrap deepEMhancer in a shell script that deactivates the CryoSPARC environment and activates the deepEMhancer one.
Replace $HOME/miniforge3 on line 17 with the path to your conda installation.
Make this file executable by the CryoSPARC user from the command line
chmod +x deepemhancer.sh
Then, when running the CryoSPARC wrapper, input the full path to deepemhancer.sh as the value for the ‘Path to deepEMhancer executable’ parameter. This file needs to be accessible at the same path from both the master and worker nodes.
To avoid having to locate and set the executable path when building every DeepEMhancer job, in v4.1 onwards you can set a project-level default that will apply to all newly created DeepEMhancer jobs.
Navigate to the projects view, select a project and choose the DeepEMhancer executable path under the 'Project Level Parameters' module within the sidebar details panel:
Volume map
half maps (map_half_A and map_half_B) or full map (map), as specified by the Use half maps parameter
Input mask (optional)
used to calculate the noise mean and standard deviation if the Normalization mode parameter is 1: Noise statistics, or provided as a binary mask if the normalization parameter is 2: Binary Mask
Sharpened volume map (map_sharp)
Path to deepEMhancer executable: full path to the deepEMhancer script, for example /home/cryosparcuser/miniforge3/envs/deepEMhancer_env/bin/deepemhancer
Path to deepEMhancer models: full path to where the deepEMhancer pretrained models were installed, for example /home/cryosparcuser/.local/share/deepEMhancerModels/production_checkpoints
Downloading and viewing the postprocessed map in a software such as UCSF Chimera, or in CryoSPARC’s built in volume viewer.
[1] R. Sanchez-Garcia, J. Gomez-Blanco, A. Cuervo et al., *“*DeepEMhancer: a deep learning solution for cryo-EM volume post-processing”, Communications Biology, vol. 4, no. 874, 2021. Available: 10.1038/s42003-021-02399-1.
Create a file in a well known location, such as the home directory (e.g., ~/deepemhancer.sh). The file should contain the following, making the noted substitutions:
For details on the other processing parameters, see the deepEMhancer , or the help command (deepemhancer -h with the conda environment activated)
Overview of the DeepEMhancer Wrapper in CryoSPARC.
