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= EMAN2.2 Release Notes = = EMAN2 Release Notes =
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This is not an all-inclusive list, it includes only the more interesting/useful changes since EMAN2.12 == Changes in the 2.3 release include ==

 * A complete CryoET pipeline from tilt series through subnanometer resolution hybrid subtomogram averaging
  * fiducial-less fully automated tilt series alignment (also works with fiducials)
  * rapid tiled Fourier reconstruction
  * full tilt/geometry aware CTF correction
  * multi class 3-D particle picker with new ties to deep-learning annotation
  * SGD automatic initial model generation
  * traditional 3-D subtomogram averaging
  * per-particle per-tilt hybrid subtomogram/single particle reconstruction to subnanometer resolution
 * A new switchable filter in e2boxer making it dramatically easier to distinguish particles in images
 * New improvements to bispectral classification for 2-D unsupervised classification and 3-D refinement
 * Focused classification in 3-D refinement available from the workflow interface
 * Improvements to e2extractsubparticles as an alternative to focused classification
 * Upgrade from Qt4 to Qt5 as part of the process of transitioning to Python3 over the next year
 * Many minor bugfixes


== Changes in the 2.21a release include ==

 * Fix bug causing "missing SNR" problem during refinement in specific situations
 * Testing support for bispectrum based class-averaging and 3-D refinement. ~10-50x faster. Better 2-D class averages
 * Better support for GPU in Neural Network tomogram segmentation and particle picking
 * Direct support for phase plates in CTF correction with adjustable phase slider and autofitting (first version, room for improvement). Issues with astigmatism in this version.
 * Better GUI display of CTF and Astigmatism
 * e2symsearch3d bugs fixed
 * Many subtomogram averaging bugs fixed. New pipeline under development.
 * Many improvements to e2evalrefine for particle and class-average assessment

== Changes from EMAN 2.12 -> EMAN 2.2 ==

EMAN2 Release Notes

Changes in the 2.3 release include

  • A complete CryoET pipeline from tilt series through subnanometer resolution hybrid subtomogram averaging
    • fiducial-less fully automated tilt series alignment (also works with fiducials)
    • rapid tiled Fourier reconstruction
    • full tilt/geometry aware CTF correction
    • multi class 3-D particle picker with new ties to deep-learning annotation
    • SGD automatic initial model generation
    • traditional 3-D subtomogram averaging
    • per-particle per-tilt hybrid subtomogram/single particle reconstruction to subnanometer resolution
  • A new switchable filter in e2boxer making it dramatically easier to distinguish particles in images
  • New improvements to bispectral classification for 2-D unsupervised classification and 3-D refinement
  • Focused classification in 3-D refinement available from the workflow interface
  • Improvements to e2extractsubparticles as an alternative to focused classification
  • Upgrade from Qt4 to Qt5 as part of the process of transitioning to Python3 over the next year
  • Many minor bugfixes

Changes in the 2.21a release include

  • Fix bug causing "missing SNR" problem during refinement in specific situations
  • Testing support for bispectrum based class-averaging and 3-D refinement. ~10-50x faster. Better 2-D class averages
  • Better support for GPU in Neural Network tomogram segmentation and particle picking
  • Direct support for phase plates in CTF correction with adjustable phase slider and autofitting (first version, room for improvement). Issues with astigmatism in this version.
  • Better GUI display of CTF and Astigmatism
  • e2symsearch3d bugs fixed
  • Many subtomogram averaging bugs fixed. New pipeline under development.
  • Many improvements to e2evalrefine for particle and class-average assessment

Changes from EMAN 2.12 -> EMAN 2.2

Single Particle Analysis

  • Many, deep improvements to refinement
    • Substantial refinement changes and new filtering techniques
    • Optional tophat filter (similar to Relion post processing), side chains often (but not always) look even better than Relion/CryoSparc
  • Local resolution and filtration
    • can be enabled in refinement to provide local detail appropriate to local resolution
  • Several new methods for conformational/compositional heterogeneity
    • Including multi-model refinement with or without alignment, masked particle subtraction, 2-D and 3-D Deep Learning approaches (experimental)
  • New bad particle identification strategy
    • Proven to produce better maps in several projects!
  • Automatic CTF
    • Used to be several manual steps. Entire process now automated.
    • Easy and fast refinement at progressive resolutions within a single project
  • Phase plate CTF correction
    • Supports phase shifts covering full 360 degree range, with explicit 'phase' slider
    • No automatic fitting of phase shift in this version (next minor release)
  • New e2boxer (particle picker)
    • Fixes the problems with the old particle picker
    • New (optional) neural network picker for difficult projects
  • Stochastic Gradient Descent initial model generator (experimental)
  • Automatic magnification anisotropy correction tool
    • Post-processing program which corrects for the common microscope anisotropy problem on FEI scopes
    • Automatic, does not require additional data collection
  • New direct detector movie aligner
    • All new program. Competitive with other alignment programs in quality
    • Workflow for handling movies in EMAN2 projects
  • New localweight averager (experimental)
    • excludes "bad" parts of individual particles (overlaps, contamination, etc.)
  • New 2-D registration algorithm
    • scales well with box size
    • more accurate going into "refine" alignment (in many cases refine can be skipped)

Subtomogram Averaging

  • New subtomogram averaging tools
    • New pipelines for subtomogram averaging and classification
  • Up to 20x faster 3-D alignments,
    • now practical to study 10,000 300x300x300 particles on a single workstation
  • New automatic missing wedge identification/compensation in alignment/averaging

Tomogram Segmentation

  • Workflow for semi-automatic tomogram annotation/segmentation
    • Uses convolutional neural network technology with user guided training of features.

Overall Changes

  • Anaconda Python based distribution
    • Integrates SciPy, Theano, PyLearn and other toolkits

  • New installers, with better OpenMPI/Pydusa support
  • GitHub

    • Source code is now managed via a public GitHub repository (cryoem/eman2)

  • Windows 10/7 64 bit
    • Initial support, poorly tested, but available for the first time (EMAN2 only, SPARX/SPHIRE do not support this platform)

EMAN2/Eman22Release (last edited 2021-03-31 03:45:14 by SteveLudtke)