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Plugin to use Relion programs within the Scipion framework

Project description

This plugin provide wrappers around several programs of RELION software suite.

PyPI release License Supported Python versions SonarCloud quality gate Downloads

prod: prod

devel: devel

support: support

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-relion
  2. Developer’s version

    • download repository

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

    scipion installp -p path_to_scipion-em-relion --devel

RELION sources will be downloaded and compiled automatically with the plugin, but you can also link an existing installation. Default installation path assumed is software/em/relion-3.1.0, if you want to change it, set RELION_HOME in scipion.conf file to the folder where the RELION is installed. If you need to use CUDA different from the one used during Scipion installation (defined by CUDA_LIB), you can add RELION_CUDA_LIB variable to the config file. Moreover, if you have to use a MPI for Relion different from Scipion MPI, you can set RELION_MPI_BIN and RELION_MPI_LIB variables in the config file.

To check the installation, simply run one of the tests. A complete list of tests can be displayed by executing scipion test --show --grep relion

Supported versions

3.1.0

We are still working towards stable plugin release, so some things might not work yet. Handling optics groups needs more testing, you are welcome to be a volunteer.

IMPORTANT: Relion-3.0 can be used with this plugin but we do not officially support it anymore, i.e. there will be no bugfixes for it.

Protocols

  • 2D classification

  • 3D auto-refine

  • 3D classification

  • 3D initial model

  • 3D multi-body

  • assign optics group

  • auto-picking

  • auto-picking LoG

  • bayesian polishing

  • center averages

  • compress movies

  • create 3d mask

  • ctf refinement

  • estimate gain to compress

  • expand symmetry

  • export coordinates

  • export ctf

  • export particles

  • local resolution

  • motion correction

  • particles extraction

  • post-processing

  • preprocess particles

  • reconstruct

  • remove preferential views

  • subtract projection

  • symmetrize volume

References

  1. Scheres et al., JMB, 2012

  2. Scheres et al., JSB, 2012

  3. Kimanius et al., eLife, 2016

  4. Zivanov et al., eLife, 2018

Project details


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