= EMAN2 Release Notes = == Changes in the 2.91 release include == === EMAN2 changes === * Full PPPT subtomogram averaging pipeline capable of near-atomic resolution * Numerous improvements for in-situ subtomogram averaging * New dedicated deep-learning tomography particle picker * Simultaneous (visual) picking of multiple macromolecular species * New options for tilt series alignment in tricky cases * Data compression support for both CryoEM and CryoET * Native HDF5 mechanism * lossless or lossy with user-selectable bit count * Files still readable by Chimera * No quality/resolution loss * Typical 10-20x size reduction, dramatically improves disk I/O and network transfer * Extensive work on e2boxer * improved deep learning picker * Fixed problems with reference-based and local pickers * Added simple inline instructions * Deep learning GMM for single particle variability studies (e2gmm.py, see arxiv paper, experimental) * New local resolution and filtration based on mFSC (Penczek), for SPA and SPT (iterative) * New visualization options for volume stacks * Support for EER format & oversampling (counting-mode Falcon 4 images) * Colored isosurfaces functioning, and automatic local resolution display when computed * Speed improvements for image I/O operations * Better integration with Numpy and Jupyter image object data sharing (advanced users) * Improved option for x/y/z projections in e2display * Drag and drop support for rearranging images in tiled image display * Python 3 based (finally!) == Changes in the 2.31 release include == === EMAN2 changes === * General changes: * New browser options for display of stacks of 3-D volumes * RCTboxer works properly again * Fixed a problem reading A/pix from FEI-style MRC files * New Processor for bit-compression of image files (makes images more compressible) * PPPT Subtomogram averaging: * Automatic CTF based handedness checking for tomograms * Focused refinement https://blake.bcm.edu/emanwiki/EMAN2/e2tomo_more#Focused_refinement * Better parallelism * Slightly improved tilt series alignment (resolution improvement) === SPHIRE 1.3 changes === * Support for processing helical specimens * AutoSPHIRE - automatic refinement tool * Integration of crYOLO * Cinderella for 2D class selection == 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)