EMAN2.2

Most of the pages are editable by any user that has registered an account on the server. To prevent spam, you need to email sludtke@bcm.edu to get an account on the system if you wish to contribute changes. If you just wish to browse, you don't need an account.

EMAN2 is the successor to EMAN1. It is a broadly based greyscale scientific image processing suite with a primary focus on processing data from transmission electron microscopes. EMAN's original purpose was performing single particle reconstructions (3-D volumetric models from 2-D cryo-EM images) at the highest possible resolution, but the suite now also offers support for single particle cryo-ET, and tools useful in many other subdisciplines such as helical reconstruction, 2-D crystallography and whole-cell tomography. EMAN2 is capable of processing very large data sets (>100,000 particle) very efficiently (up to 20x faster than EMAN1).

Please also note that this is not the (related) EMEN2 electronic notebook, but is EMAN2, a scientific image processing suite.

The official 2.2 release is still a work in progress, but should be complete by the end of Feb 2017

Please Cite

EMAN is free software, supported by NIH Grants. To keep our grant funding it is critical that you cite EMAN2 when you use it in a publication in any significant way.

• Primary EMAN2 paper:

  • G. Tang, L. Peng, P.R. Baldwin, D.S. Mann, W. Jiang, I. Rees & S.J. Ludtke. (2007) EMAN2: an extensible image processing suite for electron microscopy. J Struct Biol. 157, 38-46. PMID: 16859925

• EMAN2 high resolution refinement methods:

  • J.M. Bell, M. Chen, P.R. Baldwin & S.J. Ludtke. (2016) High Resolution Single Particle Refinement in EMAN2.1. Methods. 100, 25-34. PMID: 26931650

• Methods for analysis of conformational and compositional variability:
  • Ludtke, S. J. "Single-Particle Refinement and Variability Analysis in EMAN2.1." in Methods Enzymol 579159-189 (Elsevier, United States, 2016).
• Methods for subtomogram averaging:

  • J.G. Galaz-Montoya, C.W. Hecksel, P.R. Baldwin, E. Wang, S.C. Weaver, M.F. Schmid, S.J. Ludtke & W. Chiu. (2016) Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography. J Struct Biol. 194, 383-394. PMC4846534.

Download EMAN2

• EMAN2.2 Release Notes

• Main EMAN2 Download Page

Install EMAN2

• Installation Instructions and Tips

• Strategies for using the GUI remotely (clusters or remote workstations)

Documentation

• Live Tutorials

  • Archived video tutorials: https://www.youtube.com/c/SteveLudtke

• User Documentation

  • Tutorials (START HERE!)

  • Folders and files in an EMAN2 Project

  • File Formats, Symmetry, Box Size, ...

  • Individual Program Documentation

  • Output file descriptions and details

  • Parallel Computing (multiple cores, linux clusters, sets of workstations)

  • EMAN1 -> EMAN2 Transition Guide

  • GPGPU Computing (use the graphics processor for image processing)

  • Galleries

  • Obsolete Pages

• Advanced Users & Programmers

  • Python/C++ Programmers Documentation

  • Direct link to docs for EMData (image) class

  • Direct link to docs for Transform (orientation/Euler angle) class

  • Transitioning from CVS to Git (under construction)

• FAQ - Please ask your questions in the Google Group, answers to common questions will be posted here as well as in the Group

• Mailing list for EMAN2 discussions:

  • http://groups.google.com/group/eman2

  • eman2@googlegroups.com (must join the group before you can post)

  • http://groups.google.com/group/eman2-developers (This is the group for discussions among developers, likely less interesting for users)

About EMAN2

EMAN2 is the successor to EMAN1. It is a broadly based greyscale scientific image processing suite with a primary focus on processing data from transmission electron microscopes. EMAN's original purpose was performing single particle reconstructions (3-D volumetric models from 2-D cryo-EM images) at the highest possible resolution, but the suite now also offers support for single particle cryo-ET, and tools useful in many other subdisciplines such as helical reconstruction, 2-D crystallography and whole-cell tomography. Image processing in a suite like EMAN differs from consumer image processing packages like Photoshop in that pixels in images are represented as floating-point numbers rather than small (8-16 bit) integers. In addition, image compression is avoided entirely, and there is a focus on quantitative analysis rather than qualitative image display.

EMAN2 is now a fully usable reconstruction package, including parallelism support. However, in case you aren't ready to abandon EMAN1 yet, EMAN1 and EMAN2 can be installed in the same user account with no conflicts. All EMAN2 programs, including GUI programs, are written in the easy-to-learn Python scripting language. This permits knowledgeable end-users to customize any of the code with unprecedented ease. If you aren't an advanced user, you can still make use of the integrated GUI and all of EMAN2's command-line programs. Any programs in EMAN2 with an EMAN1 equivalent are likely substantially improved over their EMAN1 equivalents. For example e2pdb2mrc.py is ~10x faster than the EMAN1 pdb2mrc. 3-D refinements are typically 5-25x faster than in EMAN1 (with the correct options).