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Plugin to use cryoassess within the Scipion framework

Project description

This plugin provide a wrapper around Cryoassess software tools for automatic micrograph and 2D classes assessment.

PyPI release License Supported Python versions SonarCloud quality gate Downloads

prod: prod

devel: devel

Installation

You will need to use 3.0 version of Scipion to be able to run these protocols. To install the plugin, you have two options:

  1. Stable version

scipion installp -p scipion-em-cryoassess
  1. Developer’s version

    • download repository

    git clone https://github.com/scipion-em/scipion-em-cryoassess.git
    • install

    scipion installp -p path_to_scipion-em-cryoassess --devel

cryoassess binaries will be installed automatically with the plugin at software/em/cryoassess-0.1.0, but you can also link an existing installation. You also have to download training models separately (see below).

Important: you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.

Configuration variables

CONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the PATH (not recommended), which can lead to execution problems mixing scipion python with conda ones. One example of this could can be seen bellow but depending on your conda version and shell you will need something different: CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”

CRYOASSESS_ACTIVATION_CMD (default = conda activate cryoassess-0.1.0): Command to activate the cryoassess environment.

The deep-learning models can be downloaded from authors’ website and set with the following variables:

CRYOASSESS_MODEL_MIC (default = software/em/cryoassess-models/micassess_051419.h5)

CRYOASSESS_MODEL_2D (default = software/em/cryoassess-models/2dassess_062119.h5)

Verifying

To check the installation, simply run the following Scipion test:

scipion test cryoassess.tests.test_protocols_cryoassess.TestCryoassess

Supported versions

0.1.0

Protocols

  • assess micrographs

  • assess 2D classes

References

  1. High-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines. Yilai Li, Jennifer N.Cash, John J.G. Tesmer, Michael A.Cianfrocco. Structure 2020, Volume 28 (7), Pages 858-869.e3

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