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* [[Classify 3D structural heterogeneity]] | * [[Classify 3D structural heterogeneity]] | ||
* [[Refine a structure to high-resolution]] | * [[Refine a structure to high-resolution]] | ||
* [[Analyse results]] | * [[Analyse results]] : what to look out for in RELION's output files |
Revision as of 16:42, 5 October 2011
RELION (for REgularised LIkelihood OptimisatioN) is a stand-alone computer program for Maximum A Posteriori (MAP) 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. Briefly, the ill-posed problem of 3D-reconstruction is regularised by incorporating prior knowledge: the fact that macromolecular structures are smooth, i.e. they have limited power in the Fourier domain. Bayes' law uniquely determines how prior knowledge and experimental data are to be combined so that overfitting is minimised, and the optimal linear filter may be derived from the data without the need for arbitrary decisions or user expertise.
The underlying theory of MAP refinement is given in Scheres (2011). If RELION is useful in your work, please cite this paper.
Getting started
- Download & install
- Conventions & File formats
- Running RELION
- A fully guided 3D-Classification example
How To
- Preprocess images : about preparing your images: CTF correction, masking, normalisation etc
- Prepare input files : about preparing the input for RELION: STAR files or image stacks
- Calculate 2D class averages
- Classify 3D structural heterogeneity
- Refine a structure to high-resolution
- Analyse results : what to look out for in RELION's output files