EMAN is a general-purpose scientific image-processing suite developed primarily for the TEM community [1]. With over ½ million lines of Python and C++ code, hundreds of image processing algorithms and a cross-platform graphical interface, it is a capable tool for quantitative greyscale image analysis in 2-D or 3-D.Over the last three years, the Cryo-EM community has begun shifting focus from improving resolution, to validation of results. EMAN2.1 represents the results of major new developments in EMAN2's single particle reconstruction and single particle tomography workflows. The new tools such as e2refine-easy, integrate "gold standard" resolution assessment into the refinement process along with a number of new optimizations, both speeding the refinement process, and eliminating the need for empirical filtration of reconstructions by users. EMAN2.1 also integrates support for tilt-pair validation and "true resolution" testing to insure self-consistency among data and final 3-D maps. This is one of the few methods which can identify incorrect maps at low resolution.Another approach often applied to increase confidence in a 3-D structure is to reprocess the same data using multiple algorithms, preferably based on different mathematical methods. EMAN2.1 includes an interface for converting data and metadata into the appropriate format for reprocessing in Relion [2] or FreAlign[3], two alternative single particle reconstruction packages. Once these packages complete their refinements, the results can be imported back into EMAN2.1 for comparison and analysis. As an alternative, EMAN2.1 can perform the opposite process as well. A refinement completed originally in one of these other packages can be converted into an EMAN2.1 project, which can then be used to re-refine the data from scratch.Another important area of improvement is single particle tomography. Rather than the traditional approach of reconstructing large numbers of 2-D images of identical particles in random orientations, in single particle tomography, tomographic data is collected for fields of particles, producing a low resolution and incomplete, but 3-D reconstruction for each individual molecule. EMAN2.1 now incorporates tools for subtomogram extraction, and a variety of different approaches for alignement and averaging of particles. This approach is a powerful alternative to single particle analysis particularly in cases where the particles are flexible or heterogeneous in solution.EMAN2.1 also incorporates several important ease-of-use improvements. At the request of our users, the EMAN2.0 strategy for storing image data and metadata has been retired in favor of flat HDF and JSON formatted files. The project manager and file browser were both rewritten for speed and 832
EMAN (Electron Microscopy ANalysis) [3] is an open-source image processing suite in use by hundreds of researchers around the world [1][2]. We present EMAN2, a completely refactored version of this popular package. While it is primarily aimed at analysis of cryo-EM data with a particular focus on single particle reconstruction, its extensive image processing library is also applicable to other modalities such as AFM, SEM, traditional TEM, and any other imaging technique involving 1 to 3-dimensional floating point (or integer) datasets. The suite consists of a core C++ library with complete bindings to the Python scripting language. GUI tools are implemented using the cross-platform compatible WX toolkit. All computationally intensive image processing operations are implemented in C++, with user-level programs implemented as Python scripts. This language offers a vast number of features convenient for high-level scientific programming. As a very readable scripting language, this offers sophisticated end users the ability to subtly alter the functionality of any of the high level code without requiring any recompilation or C++ programming skills. Since the low level operations are performed in C++, there is virtually no performance penalty for using Python.Extensibility is an explicit part of the new library design. Rather than taking the deep object hierarchy approach used in packages like ITK, EMAN2 uses a set of simple extensible classes for specific categories of operations. Templates are provided for each type of process including: filtration, 3D reconstruction, projection, registration, comparison, etc. Adding a new algorithm requires simply defining the parameters required by your routine and inserting the actual image processing code into the template. After a simple 'make', the new algorithm is immediately available from both the C++ and Python interfaces. The modular structure integrates documentation into the code and supports full introspection for integration with GUI tools. The current library contains the expected image processing algorithms, such as Fourier and real-space filtration, various registration algorithms in addition to sophisticated new methods such as 3-D reconstruction using the gridding algorithm [4].The core library of EMAN2 is still under active development. The basic GUI widgets have been implemented (using the cross-platform WXPython toolkit), but EMAN2 does not yet have the rich end-user functionality of EMAN1. The EMAN2 core is also being used to implement SPARX, an effort to extend the PHENIX crystallography suite. EMAN2 is available for download with full source from http://ncmi.bcm.tmc.edu. Contributions by outside developers are welcome, and CVS access to the repository is available (SLudtke@bcm.edu).
Transmission Electron Microscopy (TEM), in both negative stain and cryo, is a powerful technique for determining 3-D structural information about biological molecules/ macromolecules. EMAN was originally developed a decade ago to ease the task of performing high resolution single particle reconstructions, by automating portions of the reconstruction process which were considered robust and providing an easy to use graphical user interface (GUI) for tasks not considered ready for automation [1]. The techniques used for reconstruction were a hybrid of some methods not then in common use, such as direct Fourier inversion for reconstruction and full amplitude and phase CTF correction, as well as other established techniques pioneered in earlier software packages such as SPIDER [2] and IMAGIC [3]. EMAN evolved to offer additional techniques for 2-D analysis, 2-D and 3-D population dynamics studies, and various post-processing operations such as secondary structure localization, skeletonization and crystal-structure docking. The resolution capabilities of single particle reconstruction have advanced rapidly over the last decade. In the last year, several single particle reconstructions have been solved at ~4 Å resolution, and subnanometer resolutions have been achieved in numerous labs around the world.We have just completed a ~3 year effort to develop EMAN2, a major new version of EMAN, which includes numerous new algorithms, a completely refactored C++ library and a new OpenGL-based user-interface with a complete workflow mechanism to ease the process of single particle reconstruction [4]. While small or low-resolution reconstructions can be completed on a desktop workstation, larger structures or work at high resolutions still requires more substantial computing resources. EMAN2 supports both traditional Linux clusters as well as the new GPU computing paradigm, making use of commodity 3-D graphics cards for computation. EMAN2 was designed to be highly modular, and new algorithms for specific tasks such as image alignment, similarity metrics, reconstruction, etc. can be added to the core library and immediately become available in all of the end-user programs without additional programming. While the core image processing library is written in highly efficient C++ code, all end-user programs, including the GUI interfaces are written in the Python scripting language, meaning they can be customized by knowledgeable end-users without need to recompile the entire package. EMAN2 includes a completely redesigned CTF model and automated correction scheme as well as a new semi-automated particle picking tool based on techniques developed earlier in the SWARMPS software package [5].In this talk, I will give an overview of single particle processing in general, and an introduction to EMAN2, and how it can be used to complete this, and other TEM-related tasks.
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