RELION (for REgularised LIkelihood OptimisatioN) is a stand-alone computer program for Maximum A Posteriori refinement of (multiple) 3D reconstructions or 2D class averages in cryo-electron microscopy. It is developed in the research group of Sjors Scheres at the MRC Laboratory of Molecular Biology.
The underlying theory of MAP refinement is given in a scientific publication. If RELION is useful in your work, please cite this paper.
The more comprehensive documentation of RELION is stored on the Wiki
For EER data processing, please read instructions in our wiki carefully.
More extensive options and configurations are available here, but the outlines to clone and install relion for typical use are made easy through cmake.
On Debian or Ubuntu machines, installing cmake, the compiler, and additional dependencies (mpi, fftw) is as easy as:
sudo apt install cmake git build-essential mpi-default-bin mpi-default-dev libfftw3-dev libtiff-dev
On other systems it is typically just as easy, you simply have to modify "apt" to the appropriate package manager (e.g. yum).
Once git and cmake are installed, relion can be easily installed through:
git clone https://github.com/3dem/relion.git
cd relion
git checkout master
mkdir build
cd build
cmake ..
make
By performing git checkout ver3.1 instead of git checkout master, you can access
the latest (developmental) updates for RELION 3.1.x. The code there is not
tested as throughfully as that in the master branch and not generally recommended.
The binaries will be produced in the build/bin directory. If you want to copy binaries
into somewhere else, run cmake with -DCMAKE_INSTALL_PREFIX=/where/to/install/ and
perform make install as the final step. Do not specify the build directory itself
as CMAKE_INSTALL_PREFIX! This will not work.
Also note that the MPI library used for compilation must be the one you intend to use RELION with. Compiling RELION with one version of MPI and running the resulting binary with mpirun from another version can cause crash. See our wiki below for details.
In any case, you have to make sure your PATH environmental variable points to the directory
containing relion binaries. Launching RELION as /path/to/relion is NOT a right way; this
starts the right GUI, but the GUI might invoke other versions of RELION in the PATH.
If FLTK related errors are reported, please add -DFORCE_OWN_FLTK=ON to
cmake. For FFTW related errors, try -DFORCE_OWN_FFTW=ON.
RELION also requires libtiff. Most Linux distributions have packages like libtiff-dev or libtiff-devel.
Note that you need a developer package. You need version 4.0.x to read BigTIFF files. If you installed
libtiff in a non-standard location, specify the location by
-DTIFF_INCLUDE_DIR=/path/to/include -DTIFF_LIBRARY=/path/to/libtiff.so.5.
See our wiki for more options, troubleshooting and useful environmental variables (especially in HPC clusters).
RELION is intermittently updated, with both minor and major features. To update an existing installation, simply use the following commands
cd relion
git pull
cd build
make
make install # Only when you have specified CMAKE_INSTALL_PREFIX in the cmake step
If something went wrong, remove the build directory and try again from cmake.
Parts of the cryo-EM processing pipeline can be very computationally demanding, and in some cases special hardware can be used to make these faster. There are two such cases at the moment;
- GPU acceleration: RELION only supports CUDA-capable GPUs of compute capabilty 3.5 or higher.
- Vectorized CPU code path: RELION only supports GCC and ICC 2018.3 or later.
Note that you cannot have both acceleration in the same binary at the moment.
There are more benefits than speed; the accelearated versions also have a decreased memory footprint. Details about how to enable either of these options is listed below.
Tools that are GPU-accelerated:
- relion_refine (i.e. Class2D, Class3D, Refine3D, Multibody refinement)
- relion_autopick
Classification without alignment is not accelerated.
When CUDA SDK is available, GPU support is automatically compiled.
If you run relion_refine with a the "--gpu" flag, you will run the accelerated CUDA version of the kernels.
If you leave out the "--gpu" flag, it will run the original CPU version.
Tools that are CPU-accelerated (vectorized):
- relion_refine (i.e. Class2D, Class3D, Refine3D, Multibody refinement)
Classification without alignment is not accelerated.
To build with support for CPU-accelerated kernels in addition to the original CPU version, build by setting ALTCPU=ON
cd build
rm -r *
cmake -DALTCPU=ON ..
make
make install
This will require the Intel TBB (Threading Building Blocks) library. RELION will look for TBB, and fetch and install it when it is missing on your system. You can force this behaviour (and make sure you are using the latest version) by adding:
-DFORCE_OWN_TBB=ON
In addition, you can make use the Intel Math Kernel Library (Intel MKL). This is optional (but will scale better with increased threads). Add this by:
-DMKLFFT=ON
If you run relion_refine with a the "--cpu" flag, you will run the accelerated version.
If you leave it the original CPU version will be run. You should use this flag if you can, unless you want to verify old runs or behaviour.
For details on how to compile with Intel compilers and optimal runtime configulations, please look at our wiki.