SUSAN plugin

This plugin provides wrappers for Susan software: subtomogram averaging (StA) workflow for CryoET based on sub-stacks of images instead of sub-volumes of tomograms. SUSAN uses substacks that are cropped on-the-fly from the aligned tilt-series stack and performs the CTF correction according to the selected operation (alignment or reconstruction). With this approach we decrease the computational resources needed in a typical subtomogram averaging pipeline, as we no longer need the CTF corrected stacks, the full tomogram reconstructions, or all the subtomograms in multiple binning stages.

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-susantomo

2. Developer's version

   • download repository

   git clone -b devel https://github.com/scipion-em/scipion-em-susantomo.git
   

   • install

   scipion installp -p /path/to/scipion-em-susantomo --devel
   

• SUSAN 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/susan-0.1, if you want to change it, set SUSAN_HOME in scipion.conf file to the folder where the SUSAN is installed.
• SUSAN installation requires CUDA libraries, gcc >= 9.x and cmake 3.22.x. OpenMPI is optional amd only required for running SUSAN on more than one cluster node. MATLAB is not required as this plugin uses Python API.
• If you need to use CUDA different from the one used during Scipion installation (defined by CUDA_LIB), you can add SUSAN_CUDA_LIB variable to the config file.
• If you have to use a MPI for SUSAN different from Scipion MPI, you can set SUSAN_MPI_BIN and SUSAN_MPI_LIB variables in the config file. At the moment MPI support in the plugin is not working.

Verifying

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

Supported versions

0.1

Protocols

• ctf estimation
• multi-reference alignment
• average and reconstruct
• create a subset

References

1. Sánchez RM, Mester R, Kudryashev M. Fast Cross Correlation for Limited Angle Tomographic Data. In: Felsberg M., Forssén PE., Sintorn IM., Unger J. (eds) Image Analysis. SCIA 2019. Lecture Notes in Computer Science, vol 11482. Doi: 10.1007/978-3-030-20205-7_34
2. R.M. Sánchez, R. Mester and M. Kudryashev. Fast Alignment of Limited Angle Tomograms by projected Cross Correlation. 2019 27th European Signal Processing Conference (EUSIPCO), 2019, pp. 1-5, doi: 10.23919/EUSIPCO.2019.8903041