Packages integrated in Scipion

This is a dynamic list of methods grouped by package that are present in Scipion. Some of them might come from a development environment and soon will be released.

Appion Atomstructutils Atsas Bamfordlab BSOFT CCP4 Chimera Cryoef cryomethods CryoSparc Eman2 Emxlib ESRF Gautomatch gCTF Grigoriefflab Igbmc Imagic Localrec Locscale Motioncorr Nysbc PharmacoKinetics Phenix Powerfit_scipion Relion Resmap Scipion Simple Sphire Spider Tomography Xmipp3

Appion

Appion dogpicker ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-appion.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

dogpicker (Picking)
Protocol to pick particles in a set of micrographs using appion dogpicker.

Contributors:

Atomstructutils

A Scipion plugin to manipulate atomic structure files (PDB/MMCIF)

Plugin url https://github.com/scipion-em/scipion-em-atomstructutils.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

operator
Utilities for handling PDB/mmcif atomic structure files.Current plugin utilities: (A) extract a chain from an atom structure (pdb/cif file),(B) perform union of several atomic structures

Contributors:

Atsas

Atsas ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-atsas.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

convert PDB to SAXS curve
Protocol for converting a PDB file (true atoms or pseudoatoms) into a SAXS curve. This is actually a wrapper to the program Crysol from Atsas. See documentation at: http://www.embl-hamburg.de/biosaxs/manuals/crysol.html

Contributors:

Bamfordlab

Plugin to use Bamfordlab programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-bamfordlab.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ethan picker (Picking)
ETHAN is a program for automatic detection of spherical particles from electron micrographs. The ETHAN software was written at the Department of Computer Science of University of Helsinki, Finland by Teemu Kivioja.

Contributors:

BSOFT

Bsoft ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-bsoft.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

bfilter
Wrapper around bfilter program of BSOFT.
blocres (Local resolution)
Bsoft program: blocres It calculates the local resolution map from to half maps. The method is based on a local measurement inside a mobile window.
particle picking (Picking)
Protocol to pick particles in a set of micrographs using bsoft

Contributors:

CCP4

Plugin url https://github.com/scipion-em/scipion-em-ccp4.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

CCP4ProtCoot
Description missing, might be a new development.
coot refinement
Coot is an interactive graphical application formacromolecular model building, model completionand validation. IMPORTANT: press "w" in coot to transferthe pdb file from coot to scipion '
refmac
Automatic refinement program in Fourier space of macromolecule structures regarding electron density maps. Generates files for volumes and FSCs to submit structures to EMDB

Contributors:

Chimera

Plugin to use chimera programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-chimera.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

chimera operate
This protocol provides access to Chimera and allows to save the result in Scipion framework. Execute command *scipionwrite [model #n] [refmodel #p] [saverefmodel 0|1]* from command line in order to transferm fitted pdb to scipion. Default values are model=#0, refmodel =#1 and saverefmodel 0 (false). model refers to the pdb file. refmodel to a 3Dmap
chimera restore session
This protocol opens Chimera and restores a session that has been stored each time a 3Dmap or an atomic structure by using `scipionwrite` or `scipionss` commad. Execute command *scipionwrite [model #n] [refmodel #p] [saverefmodel 0|1]* from command line in order to transfer fitted pdb to scipion. Default values are model=#0, refmodel =#1 and saverefmodel 0 (false). model refers to the pdb file. refmodel to a 3Dmap
chimera rigid fit
Protocol to perform rigid fit using Chimera. Execute command *scipionwrite [model #n] [refmodel #p] [saverefmodel 0|1]* from command line in order to transferm fitted pdb to scipion. Default values are model=#0, refmodel =#1 and saverefmodel 0 (false). model refers to the pdb file. refmodel to a 3Dmap
contacts
Identifies interatomic clashes and contacts based on van der Waals radii
model from template
Protocol to model three-dimensional structures of proteins using Modeller. Execute command *scipionwrite [model #n]* from command line in order to transfer the selected pdb to scipion. Default value is model=#0, model refers to the pdb file.

Contributors:

Cryoef

Plugin to use Cryoef program within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-cryoef.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

orientation analysis
Protocol for analysing the orientation distribution of single-particle EM data. Find more information at http://www.mrc-lmb.cam.ac.uk/crusso/cryoEF/

Contributors:

cryomethods

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtInitialVolumeSelector
Description missing, might be a new development.
ProtDirectionalPruning
Description missing, might be a new development.
Prot2DAutoClassifier
Description missing, might be a new development.
Prot3DAutoClassifier
Description missing, might be a new development.

Contributors:

Missing information!, but be sure someone has done it.

CryoSparc

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtCryoSparcInitialModel (Initial model)
Description missing, might be a new development.
ProtCryoSparcRefine3D (3D refinement)
Description missing, might be a new development.

Contributors:

Missing information!, but be sure someone has done it.

Eman2

Plugin to use EMAN2 programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-eman2.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

EmanProtBoxerNew (Picking)
Description missing, might be a new development.
EmanProtHelixBoxer (Picking)
Description missing, might be a new development.
EmanProtLocScale
Description missing, might be a new development.
EmanProtTomoBoxing
Description missing, might be a new development.
EmanProtTomoExtraction
Description missing, might be a new development.
boxer (Picking)
Semi-automated particle picker for SPA. Uses EMAN2 e2boxer.py.
boxer auto (Picking)
Automated particle picker for SPA. Uses EMAN2 (versions 2.2+) e2boxer.py
ctf auto
This protocol wraps *e2ctf_auto.py* EMAN2 program. It automates the CTF fitting and structure factor generation process.
initial model (Initial model)
This protocol wraps *e2initialmodel.py* EMAN2 program. It will take a set of class-averages/projections and build a set of 3-D models suitable for use as initial models in single particle reconstruction. The output set is theoretically sorted in order of quality (best one is numbered 1), though it's best to look at the other answers as well. See more details in: http://blake.bcm.edu/emanwiki/EMAN2/Programs/e2initialmodel
reconstruct
This protocol wraps *e2make3d.py* EMAN2 program. Reconstructs 3D volumes using a set of 2D images. Euler angles are extracted from the 2D image headers and symmetry is imposed. Several reconstruction methods are available. The fourier method is the default and recommended reconstructor.
refine 2D
This protocol wraps *e2refine2d.py* EMAN2 program. This program is used to produce reference-free class averages from a population of mixed, unaligned particle images. These averages can be used to generate initial models or assess the structural variability of the data. They are not normally themselves used as part of the single particle reconstruction refinement process, which uses the raw particles in a reference-based classification approach. However, with a good structure, projections of the final 3-D model should be consistent with the results of this reference-free analysis. This program uses a fully automated iterative alignment/MSA approach. You should normally target a minimum of 10-20 particles per class-average, though more is fine. Default parameters should give a good start, but are likely not optimal for any given system. Note that it does have the --parallel option, but a few steps of the iterative process are not parallellised, so don't be surprised if multiple cores are not always active.
refine 2D bispec
This protocol wraps *e2refine2d_bispec.py* EMAN2 program. This program is used to produce reference-free class averages from a population of mixed, unaligned particle images. These averages can be used to generate initial models or assess the structural variability of the data. They are not normally themselves used as part of the single particle reconstruction refinement process, which uses the raw particles in a reference-based classification approach. However, with a good structure, projections of the final 3-D model should be consistent with the results of this reference-free analysis. This variant of the program uses rotational/translational invariants derived from the bispectrum of each particle.
refine easy (3D refinement)
This protocol wraps *e2refine_easy.py* EMAN2 program.This is the primary single particle refinement program in EMAN2.1+.It replaces earlier programs such as e2refine.py and e2refine_evenodd.py.Major features of this program: * While a range of command-line options still exist. You should not normally specify more than a few basic requirements. The rest will be auto-selected for you. * This program will split your data in half and automatically refine the halves independently to produce a gold standard resolution curve for every step in the refinement. * An HTML report file will be generated as this program runs, telling you exactly what it decided to do and why, as well as giving information about runtime, etc while the job is still running. * The gold standard FSC also permits us to automatically filter the structure at each refinement step. The resolution you specify is a target, NOT the filter resolution.
sparx gaussian picker (Picking)
Automated particle picker for SPA. Uses Sparx gaussian picker. For more information see http://sparx-em.org/sparxwiki/e2boxer
tilt validate
This protocol wraps the *e2tiltvalidate.py* EMAN2 program. It performs tilt validation using the method described in Rosenthal and Henderson, JMB (2003).

Contributors:

Emxlib

EMX_EXPORT ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-emxlib.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

emx export
Export micrographs, coordinates or particles to EMX format. EMX is a joint initiative for data exchange format between different EM software packages.

Contributors:

ESRF

Esrf's ISPyB monitor for Scipion

Plugin url https://github.com/scipion-em/scipion-em-esrf.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtMonitorISPyB_ESRF_dev
Description missing, might be a new development.
monitor to ISPyB at the ESRF
Monitor to communicated with ISPyB system at ESRF.

Contributors:

Gautomatch

Plugin to use Gautomatch program within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-gautomatch.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

auto-picking (Picking)
Automated particle picker for SPA. Uses Gautomatch. Gautomatch is a GPU accelerated program for accurate, fast, flexible and fully automatic particle picking from cryo-EM micrographs with or without templates.

Contributors:

gCTF

Plugin to use Gctf program within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-gctf.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ctf estimation (CTF estimation)
Estimates CTF on a set of micrographs using Gctf. To find more information about Gctf go to: http://www.mrc-lmb.cam.ac.uk/kzhang
ctf refinement
Refines local CTF of a set of particles using Gctf. To find more information about Gctf go to: http://www.mrc-lmb.cam.ac.uk/kzhang

Contributors:

Grigoriefflab

Grigoriefflab ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-grigoriefflab.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ctffind4 (CTF estimation)
Estimates CTF on a set of micrographs using either ctffind3 or ctffind4 program. To find more information about ctffind4 go to: http://grigoriefflab.janelia.org/ctffind4
ctftilt (CTF estimation)
Estimates CTF on a set of tilted micrographs using ctftilt program.
frealign
Protocol to refine a 3D map using Frealign. The algorithms implementedare optimized to perform efficiently the correction for the contrasttransfer function of the microscope and refinement of three-dimensionalreconstructions.
frealign classify
Protocol to classify 3D using Frealign. Frealign employsmaximum likelihood classification for single particle electroncryo-microscopy.Particle alignment parameters are determined by maximizing ajoint likelihood that can include hierarchical priors, whileclassification is performed by expectation maximization of amarginal likelihood.
mag distortion correct
This program automatically corrects anisotropic magnification distortion using previously estimated parameters. It works on a set of movies.
mag distortion correct (coords)
This program automatically corrects anisotropic magnification distortion using previously estimated parameters. It works on a set of coordinates.
mag distortion estimate
This program automatically estimates anisotropic magnification distortion from a set of images of a standard gold shadowed diffraction grating
summovie (Movie alignment)
Summovie generates frame sums that can be used in subsequent image processing steps and optionally applies an exposure-dependent filter to maximize the signal at all resolutions in the frame averages.
unblur (Movie alignment)
Unblur is used to align the frames of movies recorded on an electron microscope to reduce image blurring due to beam-induced motion.

Contributors:

Igbmc

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtGemPicker (Picking)
Description missing, might be a new development.

Contributors:

Missing information!, but be sure someone has done it.

Imagic

Plugin to use IMAGIC programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-imagic.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

msa
This protocols wraps MSA-RUN program of IMAGIC. It calculates eigenimages (eigenvectors) and eigenvalues of a set of input aligned images using an iterative eigenvector algorithm optimized for (extremely) large data sets.
msa-classify (2D classification)
This protocols wraps MSA-CLASSIFY program of IMAGIC. It is based on variance-oriented hierarchical ascendant classification program (an enhanced Ward-type algorithm).

Contributors:

Localrec

Localrec ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-localrec.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

filter_subunits
This protocol mainly filters output particles from two protocols: extend symmetry and localized subparticles. It can filter the particles (sub-particles) according to spatial distance, view, and angular distance.
localized extraction
Extract computed sub-particles from a SetOfParticles.
localized subparticles (3D refinement)
This class contains a re-implementation to a method for the localized three-dimensional reconstruction of such subunits. After determining the particle orientations, local areas corresponding to the subunits can be extracted and treated as single particles.

Contributors:

Locscale

Locscale ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-locscale.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

locscale
This Protocol computes contrast-enhanced cryo-EM maps by local amplitude scaling using a reference model.

Contributors:

Motioncorr

Plugin to use motioncorr programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-motioncorr.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

movie alignment (Movie alignment)
This protocol wraps motioncor2 movie alignment program developed at UCSF. Motioncor2 performs anisotropic drift correction and dose weighting (written by Shawn Zheng @ David Agard lab)

Contributors:

Nysbc

Plugin to use NYSBC programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-nysbc.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

3D FSC
Protocol to calculate 3D FSC. 3D FSC is software tool for quantifying directional resolution using 3D Fourier shell correlation volumes. Find more information at https://github.com/nysbc/Anisotropy

Contributors:

PharmacoKinetics

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtPKPDDissolutionFit
Description missing, might be a new development.
ProtPKPDODESimulate
Description missing, might be a new development.
ProtPKPDODETwoVias
Description missing, might be a new development.
ProtPKPDTwoCompartmentsUrine
Description missing, might be a new development.
XmippProtAnalyzeLocalCTF
Description missing, might be a new development.
ProtPKPDFilterPopulation
Description missing, might be a new development.
ProtPKPDApplyAllometricScaling
Description missing, might be a new development.
ProtPKPDCreateLabel
Description missing, might be a new development.
ProtPKPDImportFromCSV
Description missing, might be a new development.
ProtPKPDNCAIVObs
Description missing, might be a new development.
ProtPKPDGenericFit
Description missing, might be a new development.
ProtPKPDMonoCompartmentUrine
Description missing, might be a new development.
ProtPKPDAllometricScaling
Description missing, might be a new development.
ProtPKPDSimulateDrugInteractions
Description missing, might be a new development.
ProtPKPDTwoCompartmentsClint
Description missing, might be a new development.
ProtPKPDFilterMeasurements
Description missing, might be a new development.
ProtImportExperiment
Description missing, might be a new development.
ProtPKPDNCAEV
Description missing, might be a new development.
ProtPKPDStatisticsLabel
Description missing, might be a new development.
ProtPKPDTwoCompartments
Description missing, might be a new development.
ProtPKPDExportToCSV
Description missing, might be a new development.
ProtPKPDMonoCompartmentClint
Description missing, might be a new development.
ProtPKPDChangeUnits
Description missing, might be a new development.
ProtPKPDEliminationRate
Description missing, might be a new development.
ProtPKPDAbsorptionRate
Description missing, might be a new development.
ProtPKPDMonoCompartment
Description missing, might be a new development.
ProtPKPDMonoCompartmentPD
Description missing, might be a new development.
ProtPKPDODEBootstrap
Description missing, might be a new development.
ProtPKPDTwoCompartmentsBothPD
Description missing, might be a new development.
ProtPKPDTwoCompartmentsBoth
Description missing, might be a new development.
ProtPKPDTwoCompartmentsClintMetabolite
Description missing, might be a new development.
ProtPKPDFitBootstrap
Description missing, might be a new development.
BatchProtCreateExperiment
Description missing, might be a new development.
ProtPKPDDissolutionF2
Description missing, might be a new development.
ProtPKPDDeconvolve
Description missing, might be a new development.
ProtPKPDChangeVia
Description missing, might be a new development.

Contributors:

Missing information!, but be sure someone has done it.

Phenix

Plugin url https://github.com/scipion-em/scipion-em-phenix.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

PhenixProtAutomatedSharpening
Description missing, might be a new development.
emringer
EMRinger is a Phenix application to validate the agreement betweenthe initial map and the derived low-resolution atomic structure. This programsamples the density around Chi1 angles of protein sidechains. Electronicdensity and appropriate rotameric angles must coincide for each residue ifthe atomic structure backbone has been perfectly fitted to the map.
molprobity
MolProbity is a Phenix application to validate the geometry of anatomic structure inferred from an electron density map.
real space refine
Tool for extensive real-space refinement of an atomic structure against the map provided. The map can be derived from X-ray or neutron crystallography, or cryoEM. The program obtains a model that fits the map as well as possible having appropriate geometry. The model should not show validation outliers, such as Ramachandran plot or rotamer outliers.
refinementBase
MolProbity is a Phenix application to validate the geometry of anatomic structure derived from a cryo-EM density map.
superpose pdbs
Superpose two PDBs so that they optimally match

Contributors:

Powerfit_scipion

Powerfit ready to use in Scipion.

Plugin url https://github.com/scipion-em/scipion-em-powerfit.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

powerfit
Protocol for fitting a PDB into a 3D volume This is actually a wrapper to the program Powerfit. See documentation at: http://www.bonvinlab.org/education/powerfit

Contributors:

Relion

Plugin to use Relion programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-relion.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtRelionAutopick (Picking)
Description missing, might be a new development.
ProtRelionAutopickFom (Picking)
Description missing, might be a new development.
2D classification (2D classification)
This protocol runs Relion 2D classification.
3D auto-refine (3D refinement)
Protocol to refine a 3D map using Relion.Relion employs an empirical Bayesian approach to refinementof (multiple) 3D reconstructionsor 2D class averages in electron cryo-microscopy (cryo-EM). Manyparameters of a statistical model are learned from the data,whichleads to objective and high-quality results.
3D classification
Protocol to classify 3D using Relion Bayesian approach. Relion employs an empirical Bayesian approach to refinement of (multiple) 3D reconstructions or 2D class averages in electron cryo-EM. Many parameters of a statistical model are learned from the data, which leads to objective and high-quality results.
3D initial model (Initial model)
This protocols creates a 3D initial model using Relion. Generate a 3D initial model _de novo_ from 2D particles using Relion Stochastic Gradient Descent (SGD) algorithm.
3D multi-body
Relion protocol for multi-body refinement. This approach models flexible complexes as a user-defined number of rigid bodies that move independently from each other. Using separate focused refinements with iteratively improved partial signal subtraction, improved reconstructions are generated for each of the defined bodies. Moreover, using PCA on the relative orientations of the bodies over all particle images in the data set, we generate movies that describe the most important motions in the data.
auto-picking (Picking)
This protocol runs Relion autopicking (version 2.0+). This Relion protocol uses the 'relion_autopick' program to pick particles from micrographs, either using templates or gaussian blobs. The picking with this protocol is divided in three steps: 1) Run with 'Optimize' option for several (less than 30) micrographs. 2) Execute the wizard to refine the picking parameters. 3) Run with 'Pick all' option to pick particles from all micrographs. The first steps will use internally the option '--write-fom-maps' to write to disk the FOM maps. The expensive part of this calculation is to calculate a probability-based figure-of-merit (related to the cross-correlation coefficient between each rotated reference and all positions in the micrographs. That's why it is only done in an small subset of the micrographs, where one should use representative micrographs for the entire data set, e.g. a high and a low-defocus one, and/or with thin or thick ice. Step 2 uses a much cheaper peak-detection algorithm that uses the threshold and minimum distance parameters.
auto-picking LoG (Picking)
This Relion protocol uses 'relion_autopick' program for the Laplacian of Gaussian (LoG) option.
bayesian polishing
Wrapper protocol for the Relion's Bayesian Polishing. As of release 3.0, Relion also implements a new Bayesian approach to beam induced motion correction. This approach aims to optimise a regularised likelihood, which allows us to associate with each hypothetical set of particle trajectories a prior likelihood that favors spatially coherent and temporally smooth motion without imposing any hard constraints. The smoothness prior term requires three parameters that describe the statistics of the observed motion. To estimate the prior that yields the best motion tracks for this particular dataset, we can first run the program in 'training mode'. Once the estimates have been obtained, one can then run the program again to fit tracks for the motion of all particles in the data set and to produce adequately weighted averages of the aligned movie frames.
center averages
Align class averages by their center of mass using *relion_image_handler*. (With *--shift_com* option)
create 3d mask
This protocols creates a 3D mask using Relion. The mask is created from a 3d volume or by comparing two input volumes.
ctf refinement
Wrapper protocol for the Relion's per-particle CTF refinement.
expand symmetry
This protocols wraps relion_particle_symmetry_expand program. Given an input set of particles with angular assignment, expand the set by applying a pseudo-symmetry. Be aware that input symmetry values follow Xmipp conventions as described in: http://xmipp.cnb.csic.es/twiki/bin/view/Xmipp/Symmetry
export ctf
Export a SetOfCTF to a Relion STAR file.
export particles
Export particles from Relion to be used outside Scipion.
local resolution (Local resolution)
This protocol does local resolution estimation using Relion. This program basically performs a series of post-processing operations with a small soft, spherical mask that is moved over the entire map, while using phase-randomisation to estimate the convolution effects of that mask.
motioncor (Movie alignment)
Wrapper for the Relion's implementation of motioncor algorithm.
movie particles extraction
Protocol to extract particles from a set of coordinates
particle polishing
This protocols runs particle polishing using Relion. This Relion protocol tracks particle movement in movie frames (from previous movie refinement run), applies a resolution and dose-dependent weighting scheme for each frame and finally sums them together, producing so-called shiny, or polished particles.
particles extraction
Protocol to extract particles using a set of coordinates.
post-processing
Relion post-processing protocol for automated masking, overfitting estimation, MTF-correction and B-factor sharpening.
preprocess particles
This protocol wraps relion_preprocess program. It is used to perform normalisation, filtering or scaling of the particles.
reconstruct
This protocol reconstructs a volume using Relion. Reconstruct a volume from a given set of particles. The alignment parameters will be converted to a Relion star file and used as direction projections to reconstruct.
sort particles
Relion particle sorting protocol. It calculates difference images between particles and their aligned (and CTF-convoluted) references, and produces Z-score on the characteristics of these difference images (such as mean, standard deviation, skewness, excess kurtosis and rotational symmetry).
subtract projection
Signal subtraction protocol of Relion. Subtract volume projections from the experimental particles. The particles must have projection alignment in order to properly generate volume projections.
symmetrize volume
Symmetrize a volume using Relion programs: *relion_align_symmetry* and *relion_image_handler*.

Contributors:

Resmap

Resmap ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-resmap.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

local resolution (Local resolution)
ResMap is software tool for computing the local resolution of 3D density maps studied in structural biology, primarily by cryo-electron microscopy (cryo-EM). Please find the manual at http://resmap.sourceforge.net

Contributors:

Scipion

Plugin url https://github.com/I2PC/scipion.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtImportFilaments
Description missing, might be a new development.
LegacyProtocol
Description missing, might be a new development.
2d streamer
This protocol will monitor an input set of particles (usually in streaming) and will run/schedule many copies of a given 2D classification protocol but using subsets of the input particles as the 2D classification input.
ProtCreateFSC
Description missing, might be a new development.
ProtCreateMask
Description missing, might be a new development.
ProtUserSubSet
Create subsets from the GUI. This protocol will be executed mainly calling the script 'pw_create_image_subsets.py' from the ShowJ gui. The enabled/disabled changes will be stored in a temporary sqlite file that will be read to create the new subset.
assign alignment
Assign a the alignment calculated for a set of particles to another set. This protocol will take into account the differences of pixel size (A/pix) between the two sets and multiply by the right factor the shifts. The particles with the alignment can also be a subset of the other images
assign ctf
This protocol assigns a CTF estimation to a particular set of particles producing a new set.
assign gain to movies
Assign a gain image to a set of movies
average frames
Very simple protocol to align all the frames of a given data collection session. It can be used as a sanity check.
classes consensus
Compare two SetOfClasses
create stream data
create setofXXXX in streaming mode. micrograph -> read a micrograph in memory and writes it nDim times movie -> read a movie in memory and writes it nDim times randomMicrographs -> creates a micrograph with random values and aplies a random CTF particles -> read nDim particles in memory and writes it in streaming
ctf monitor
check CPU, mem and IO usage.
export emdb
generates files for volumes and FSCs to submit structures to EMDB
extract coordinates
Extract the coordinates information from a set of particles. This protocol is useful when we want to re-extract the particles (maybe resulting from classification and cleaning) with the original dimensions. It can be also handy to visualize the resulting particles in their location on micrographs.
import atomic structure
Protocol to import an atomic structure to the project.Format may be PDB or MMCIF
import averages
Protocol to import a set of averages to the project
import coordinate pairs
Protocol to import a set of tilt pair coordinates
import coordinates
Protocol to import a set of coordinates
import ctf
Common protocol to import a set of ctfs into the project
import mask
Class for import masks from existing files.
import micrographs
Protocol to import a set of micrographs to the project
import movies
Protocol to import a set of movies (from direct detector cameras) to the project.
import particles
Protocol to import a set of particles to the project
import sequence
Protocol to import an aminoacid/nucleotide sequence file to the project
import tilted micrographs
Protocol to import untilted-tilted pairs of micrographs in the project
import volumes
Protocol to import a set of volumes to the project
join sets
Protocol to join two or more sets of images. This protocol allows to select two or more set of images and will produce another set joining all elements of the selected sets. It will validate that all sets are of the same type of elements (Micrographs, Particles or Volumes)
monitor summary
Provide some summary of the basic steps of the Scipion-Box: - Import movies - Align movies (global and/or local) - CTF estimation - Movie gain estimation.
movie gain monitor
check CPU, mem and IO usage.
parallel test
A parallel test protocol.
particles subset by micrograph
Create a subset of those particles comes from a particular set of micrographs
pdf report
Produce a pdf report from the files in a given directory. Supported file formats: *.tex, *.txt, *.jpg, *.png, *.pdf Files in the directory are sorted by name alphabetically, so if you want them to have the right order a possibility is to name them as 0010-myText.txt 0020-aFigure.png 0030-anotherFigure.jpg 0040-aPaper.pdf 0050-anotherText.tex ... when these files are sorted, they will be sorted by the number in front.
picking difference
Protocol to compute the difference between a reference SetOfPartices and a another set (usually a negative reference). The output will be a SetOfCoordinates with the particles in the reference input that are not close to coordinates in the negative input.
split sets
Protocol to split a set in two or more subsets.
stress
stress will stress test a computer system in various selectable ways. Several options require the program stress-ng.
subset
Create a set with the elements of an original set that are also referenced in another set. Usually there is a bigger set with all the elements, and a smaller one obtained from classification, cleaning, etc. The desired result is a set with the elements from the original set that are also present somehow in the smaller set (in the smaller set they may be downsampled or processed in some other way). Both sets should be of the same kind (micrographs, particles, volumes) or related (micrographs and CTFs for example).
system_monitor
check CPU, mem and IO usage.
test output
Protocol to test scalar output and input linking

Contributors:

Simple

Plugin to use Simple programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-simple.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtPrime25
Description missing, might be a new development.
ProtPrime2D (2D classification)
Description missing, might be a new development.
ProtPrime3D (3D refinement)
Description missing, might be a new development.
prime
Produces one or several initial volumes using simple prime

Contributors:

Sphire

Sphire ready to use in scipion.

Plugin url https://github.com/scipion-em/scipion-em-sphire.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtISAC (2D classification)
Description missing, might be a new development.
SphireProt2DAlign (2D classification)
Description missing, might be a new development.
SphireProtCRYOLO (Picking)
Description missing, might be a new development.
cryolo picking
Picks particles in a set of micrographs either manually or in a supervised mode.
cryolo training
Picks particles in a set of micrographs either manually or in a supervised mode.

Contributors:

Spider

Plugin to use Spider programs within the Scipion framework

Plugin url https://github.com/scipion-em/scipion-em-spider.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

align ap sr
This protocol wraps SPIDER AP SR command. Reference-free alignment (both translational and rotational) of an image series. See detailed description at: [[http://spider.wadsworth.org/spider_doc/spider/docs/man/apsr.html][SPIDER's AP SR online manual]]
align pairwise
This protocol wraps SPIDER AP SR command (pairwise alignment). Reference-free alignment (both translational and rotational) of an image series. This alignment scheme aligns a pair of images at a time and then averages them. Then, the averages of each of those pairs are aligned and averaged, and then pairs of those pairs, etc. Compared to [[http://spider.wadsworth.org/spider_doc/spider/docs/man/apsr.html][AP SR]], this alignment scheme appears to be less random, which chooses seed images as alignment references. For more information, see Step 2b at [[http://spider.wadsworth.org/spider_doc/spider/docs/techs/MSA/index.html#pairwise][SPIDER's MDA online manual]]
ca pca
Protocol for Correspondence Analysis (CA) or Principal Component Analysis (PCA). CA is the preferred method of finding inter-image variations. PCA computes the distance between data vectors with Euclidean distances, while CA uses Chi-squared distance. CA is superior because it ignores differences in exposure between images, eliminating the need to rescale between images. In contrast, PCA seems to be more robust: less likely to be trapped in an infinite loop of numerical inaccuracy. For more info see: [[http://spider.wadsworth.org/spider_doc/spider/docs/techs/classification/tutorial.html#CAPCA][SPIDER MDA documentation]]
classify diday (2D classification)
This protocol wraps SPIDER CL CLA command. Performs automatic clustering using Diday's method and Hierarchical Ascendant Classification (HAC) using Ward's criterion on factors produced by CA or PCA.
classify kmeans (2D classification)
This protocol wraps SPIDER CL KM command. Performs automatic K-Means clustering and classification on factors produced by CA or PCA.
classify ward (2D classification)
This protocol wraps SPIDER CL HC command. Finds clusters of images/elements in factor space (or a selected subspace) by using Diday's method of moving centers, and applies hierarchical ascendant classification (HAC) (using Ward's method) to the resulting cluster centers.
create 2d mask
This protocol creates a 2D mask using SPIDER. In the step following this one, dimension-reduction, the covariance of the pixels in all images will be computed. Only pixels under a given mask will be analyzed. If this step is performed, a mask that follows closely the contour the particle of interest will be used. Absent a custom-made mask, a circular mask will be used. For non-globular structures, this customized mask will reduce computational demand and the likelihood of numerical inaccuracy in the next dimension-reduction step. On the other hand, given the power of modern computers, this step may be unnecessary.
filter particles
Apply Fourier filters to an image or a volume using Spider FQ or FQ NP. To improve boundary quality the image is padded with the average value to twice the original size during filtration if padding is selected. See more documentation at: [[http://spider.wadsworth.org/spider_doc/spider/docs/man/fq.html][SPIDER's FQ online manual]]
reconstruct fourier
This protocol wraps SPIDER BP 32F command. Simple reconstruction protocol using Fourier back projection. Mainly used for testing conversion of Euler angles.
refine 3D (3D refinement)
Reference-based refinement using SPIDER AP SHC and AP REF commands. Iterative refinement improves the accuracy in the determination of orientations. This improvement is accomplished by successive use of more finely-sampled reference projections. Two different workflows are suggested: with defocus groups or without (gold-standard refinement). For more information, see: [[http://spider.wadsworth.org/spider_doc/spider/docs/techs/recon/mr.html][SPIDER documentation on projection-matching]]

Contributors:

Tomography

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

ProtTsMotionCorr
Description missing, might be a new development.
ProtImportTiltSeries
Description missing, might be a new development.
ProtImportTomograms
Description missing, might be a new development.
ProtTsCtffind
Description missing, might be a new development.
ProtImodAuto3D
Description missing, might be a new development.
ProtImodEtomo
Description missing, might be a new development.
ProtImportSubTomograms
Description missing, might be a new development.

Contributors:

Missing information!, but be sure someone has done it.

Xmipp3

Plugin to use Xmipp programs within the Scipion framework.

Plugin url https://github.com/i2pc/scipion-em-xmipp.

Available in Linux. Scientific software, Image processing, cryo em

Available methods:

XmippProtReAlignClasses
Description missing, might be a new development.
XmippProtDirectionalClasses
Description missing, might be a new development.
XmippProtLocalCTF (CTF estimation)
Estimates particle CTF
XmippProtAlignmentNMAVol
Description missing, might be a new development.
XmippProtDimredNMAVol
Description missing, might be a new development.
XmippProtCombinePdb
Description missing, might be a new development.
XmippProtDirectionalPruning
Description missing, might be a new development.
XmippProtVolumeOccupancy
Description missing, might be a new development.
XmippProtEliminateFalseParticles
Description missing, might be a new development.
XmippProtDl2r
Description missing, might be a new development.
XmippProtScreenDeepLearning1
Description missing, might be a new development.
XmippProtAngularAlignmentSPH
Description missing, might be a new development.
XmippProtCTFSelection
Description missing, might be a new development.
XmippProtVolumeHomogenizer
Description missing, might be a new development.
XmippProtCTFDiscrepancy
Description missing, might be a new development.
XmippProtPrepareDeepConsensus
Description missing, might be a new development.
XmippProtHelicalSymmetrize
Description missing, might be a new development.
2D kmeans clustering
Classifies a set of particles using a clustering algorithm to subdivide the original dataset into a given number of classes.
3d bionotes
Protocol for checking annotations This is actually a wrapper to 3D Bionotes. See documentation at: http://3dbionotes.cnb.csic.es
XmippProtDeepConsSubSet
Create subsets from the GUI for the Deep Consensus protocol. This protocol will be executed mainly calling the script 'pw_create_image_subsets.py' from the ShowJ gui. The enabled/disabled changes will be stored in a temporary sqlite file that will be read to create the new subset.
add noise particles
Given a set of particles, the protocol will add noise to them The types of noise are Uniform, Student and Gaussian.
add noise volume/s
Given a set of volumes, or a volume the protocol will add noise to them The types of noise are Uniform, Student and Gaussian.
align volume
Aligns a set of volumes using cross correlation or a Fast Fourier method.
align volume and particles
Aligns a volume (inputVolume) using a Fast Fourier method with respect to a reference one (inputReference). The obtained alignment parameters are used to align the set of particles (inputParticles) that generated the input volume.
align volume web
Aligns a set of volumes using cross correlation. Based on Xmipp protocol for aligning volumes, but the parameters are restricted for ease of use.
align with cl2d
Aligns a set of particles using the CL2D algorithm.
apply 2d mask
Apply mask to a set of particles
apply 3d mask
Apply mask to a volume
apply alignment 2d
Apply alignment parameters and produce a new set of images.
apply transformation matrix
Apply transformation matrix of an aligned volume on a set of particles to modify their angular assignment. Note: These particles are practically related to the aligned volume (but before alignment).
assign tiltpairs
From two sets of points (tilted and untilted) the protocol determines the affine transformation between these sets.
auto-picking (step 2) (Picking)
Protocol to pick particles automatically in a set of micrographs using previous training
break symmetry
Given an input set of particles with angular assignment, find an equivalent angular assignment for a given symmetry. Be aware that input symmetry values follows Xmipp conventions as described in: http://xmipp.cnb.csic.es/twiki/bin/view/Xmipp/Symmetry
calculate strain
Compare two states of a volume to analyze the local strains and rotations
center particles
Realignment of un-centered particles.
cl2d (2D classification)
Classifies a set of images using a clustering algorithm to subdivide the original dataset into a given number of classes.
cltomo
Averages a set of subtomograms taking into account the missing edge.
compare angles
Compare two sets of angles. The output is a list of all common particles with the angular difference between both assignments. The output is constructed by keeping the information from the Set 1 and adding the shiftDiff and angularDiff.
compare reprojections
Compares a set of classes or averages with the corresponding projections of a reference volume. The set of images must have a 3D angular assignment and the protocol computes the residues (the difference between the experimental images and the reprojections). The zscore of the mean and variance of the residues are computed. Large values of these scores may indicate outliers. The protocol also analyze the covariance matrix of the residual and computes the logarithm of its determinant [Cherian2013]. The extremes of this score (called zScoreResCov), that is values particularly low or high, may indicate outliers.
consensus classes 3D
Compare several SetOfClasses3D. Return the intersection of the input classes.
convert a PDB
Convert a PDB file into a volume.
convert to pseudoatoms
Converts an EM volume into pseudoatoms
correlation alignment (Movie alignment)
Wrapper protocol to Xmipp Movie Alignment by cross-correlation
create 2d mask
Create a 2D mask. The mask can be created with a given geometrical shape (Circle, Rectangle, Crown...) or it can be obtained from operating on a 2d image or a previuous mask.
create 3d mask
Create a 3D mask. The mask can be created with a given geometrical shape (Sphere, Box, Cylinder...) or it can be obtained from operating on a 3d volume or a previuous mask.
create gallery
Create a gallery of projections from a volume. This gallery of projections may help to understand the images observed in the microscope.
crop/resize particles
Crop or resize a set of particles
crop/resize volumes
Crop or resize a set of volumes
ctf consensus
Protocol to make a selection of meaningful CTFs in basis of the defocus values, the astigmatism, the resolution, other Xmipp parameters, and the agreement with a secondary CTF for the same set of micrographs.
ctf estimation (CTF estimation)
Protocol to estimate CTF on a set of micrographs using Xmipp.
ctf_correct_wiener2d
Perform CTF correction by Wiener filtering.
deep consensus picking
Protocol to compute a smart consensus between different particle picking algorithms. The protocol takes several Sets of Coordinates calculated by different programs and/or different parameter settings. Let's say: we consider N independent pickings. Then, a neural network is trained using different subset of picked and not picked cooridantes. Finally, a coordinate is considered to be a correct particle according to the neural network predictions.
deep denoising
Description missing, might be a new development.
defocus group
Given a set of CTFs group them by defocus value. The output is a metadata file containing a list of defocus values that delimite each defocus group.
denoise particles
Remove particles noise by filtering them. This filtering process is based on a projection over a basis created from some averages (extracted from classes). This filtering is not intended for processing particles. The huge filtering they will be passed through is known to remove part of the signal with the noise. However this is a good method for clearly see which particle are we going to process before it's done.
directional ResDir
Given a map the protocol assigns local resolutions to each voxel of the map.
eliminate empty classes
Takes a set of classes and using statistical methods (variance of variances of sub-parts of input image) eliminates those samples, where there is no object/particle (only noise is presented there). Threshold parameter can be used for fine-tuning the algorithm for type of data.
eliminate empty particles
Takes a set of particles and using statistical methods (variance of variances of sub-parts of input image) eliminates those samples, where there is no object/particle (only noise is presented there). Threshold parameter can be used for fine-tuning the algorithm for type of data.
enrich
Method to get two volume from different classes (with different conformation) and correcting (deforming) all images of one of the volumes (input volume) with respect to the another one as a reference, using optical flow algorithm. The output is a setOfParticles contaied deformed reference particles.
extract movie particles
Extract a set of Particles from each frame of a set of Movies.
extract particle pairs
Protocol to extract particles from a set of tilted pairs coordinates
extract particles
Protocol to extract particles from a set of coordinates
extract unit cell
generates files for volumes and FSCs to submit structures to EMDB
filter particles
Apply Fourier filters to a set of particles
filter volumes
Apply Fourier filters to a set of volumes
generate reprojections
Compares a set of classes or averages with the corresponding projections of a reference volume. The set of images must have a 3D angular assignment and the protocol computes the residues (the difference between the experimental images and the reprojections). The zscore of the mean and variance of the residues are computed. Large values of these scores may indicate outliers. The protocol also analyze the covariance matrix of the residual and computes the logarithm of its determinant [Cherian2013]. The extremes of this score (called zScoreResCov), that is values particularly low or high, may indicate outliers.
gl2d (2D classification)
2D alignment using Xmipp GPU Correlation algorithm.
gl2d static
2D alignment in semi streaming using Xmipp GPU Correlation. A previous set of classes must be provided to include the new images in the corresponding class although the representatives will be maintained.
gl2d streaming (2D classification)
2D alignment in full streaming using Xmipp GPU Correlation. The set of classes will be growing whilst new particle images are received.
helical symmetry
Estimate helical parameters and symmetrize. Helical symmetry is defined as V(r,rot,z)=V(r,rot+k*DeltaRot,z+k*Deltaz).
highres (3D refinement)
This is a 3D refinement protocol whose main input is a volume and a set of particles. The set of particles has to be at full size (the finer sampling rate available), but the rest of inputs (reference volume and masks) can be at any downsampling factor. The protocol scales the input images and volumes to a reasonable size depending on the resolution of the previous iteration. The protocol works with any input volume, whichever its resolution, as long as it is a reasonable initial volume for the set of particles. The protocol does not resolve the heterogeneous problem (it assumes an homogeneous population), although it is somewhat tolerant through the use of particle weights in the reconstruction process. It is recommended to perform several global alignment iterations before entering into the local iterations. The switch from global to local should be performed when a substantial percentage of the particles do not move from one iteration to the next. The algorithm reports the cross correlation (global alignment) or cost (local) function per defocus group, so that we can see which was the percentile of each particle in its defocus group. You may want to perform iterations one by one, and remove from one iteration to the next, those particles that worse fit the model.
kerdensom
Classifies a set of images using Kohonen's Self-Organizing Feature Maps (SOM) and Fuzzy c-means clustering technique (FCM) . The kerdenSOM algorithm anneals from an initial high regularization factor to a final lower one, in a user-defined number of steps. KerdenSOM is an excellent tool for classification, especially when using a large number of data and classes and when the transition between the classes is almost continuous, with no clear separation between them. The input images must be previously aligned.
local MonoRes (Local resolution)
Given a map the protocol assigns local resolutions to each voxel of the map.
local MonoTomo
Given a map the protocol assigns local resolutions to each voxel of the map.
localdeblur sharpening (3D refinement)
Given a resolution map the protocol calculate the sharpened map.
manual-picking (step 1) (Picking)
Picks particles in a set of micrographs either manually or in a supervised mode.
metaprotocol heterogeneity
Metaprotocol to run together all the protocols to discover discrete heterogeneity in a set of particles
metaprotocol heterogeneity output
Metaprotocol to run together all the protocols to discover discrete heterogeneity in a set of particles
metaprotocol heterogeneity subset
Metaprotocol to select a set of particles from a 3DClasses and a Volume from a SetOfVolumes
ml2d
Perform (multi-reference) 2D-alignment using a maximum-likelihood ( *ML* ) target function. Initial references can be generated from random subsets of the experimental images or can be provided by the user (this can introduce bias). The output of the protocol consists of the refined 2D classes (weighted averages over all experimental images). The experimental images are not altered at all. Although the calculations can be rather time-consuming (especially for many, large experimental images and a large number of references we strongly recommend to let the calculations converge.
mltomo
Align and classify 3D images with missing data regions in Fourier space, e.g. subtomograms or RCT reconstructions, by a 3D multi-reference refinement based on a maximum-likelihood (ML) target function. See http://xmipp.cnb.csic.es/twiki/bin/view/Xmipp/Ml_tomo_v31 for further documentation
movie average (Movie alignment)
Protocol to average movies
movie gain
Estimate the gain image of a camera, directly analyzing one of its movies.
movie maxshift
Protocol to make an automatic rejection of those movies whose frames move more than a given threshold. Rejection criteria: - *by frame*: Rejects movies with drifts between frames bigger than a certain maximum. - *by whole movie*: Rejects movies with a total travel bigger than a certain maximum. - *by frame and movie*: Rejects movies if both conditions above are met. - *by frame or movie*: Rejects movies if one of the conditions above are met.
movie resize
Resize a set of movies. Only downsampling is allowed.
multiple fscs
Compute the FSCs between a reference volume and a set of input volumes. A mask can be provided and the volumes are aligned by default.
multireference alignability
Performs soft alignment validation of a set of particles confronting them against a given 3DEM map. This protocol produces particle alignment precision and accuracy parameters.
nma alignment
Protocol for flexible angular alignment.
nma analysis
Flexible angular alignment using normal modes
nma cluster
Protocol executed when a cluster is created from NMA images and theirs deformations.
nma dimred
This protocol will take the images with NMA deformations as points in a N-dimensional space (where N is the number of computed normal modes) and will project them in a reduced spaced (usually with less dimensions).
normalize strain
Normalize the local strain and rotations amongst several runs
operate particles
Apply an operation to two sets of particles
operate volumes
Apply an operation to two sets of volumes
optical alignment
Wrapper protocol to Xmipp Movie Alignment by Optical Flow
optical alignment (Movie alignment)
Wrapper protocol to Xmipp Movie Alignment by Optical Flow
particle boxsize
Given a set of micrographs, the protocol estimate the particle box size.
pick noise
Protocol to pick noise particles
picking consensus
Protocol to estimate the agreement between different particle picking algorithms. The protocol takes several Sets of Coordinates calculated by different programs and/or different parameter settings. Let's say: we consider N independent pickings. Then, a coordinate is considered to be a correct particle if M pickers have selected the same particle (within a radius in pixels specified in the form). If you want to be very strict, then set M=N; that is, a coordinate represents a particle if it has been selected by all particles (this is the default behaviour). Then you may relax this condition by setting M=N-1, N-2, ... If you want to be very flexible, set M=1, in this way it suffices that 1 picker has selected the coordinate to be considered as a particle. Note that in this way, the cleaning of the dataset has to be performed by other means (screen particles, 2D and 3D classification, ...).
preprocess micrographs
Protocol to preprocess a set of micrographs in the project. You can crop borders, remove bad pixels, etc.
preprocess particles
Preprocess a set of particles. You can remove dust, normalize, apply threshold, etc
preprocess volumes
Protocol for Xmipp-based preprocess for volumes
projection matching (3D refinement)
3D reconstruction and classification using multireference projection matching
random conical tilt
Creates initial volumes by using a set of projections/classes from a tilted-pair picking process and using RCT algorithm.
ransac (Initial model)
Computes an initial 3d model from a set of projections/classes using RANSAC algorithm. This method is based on an initial non-lineal dimensionality reduction approach which allows to select representative small sets of class average images capturing the most of the structural information of the particle under study. These reduced sets are then used to generate volumes from random orientation assignments. The best volume is determined from these guesses using a random sample consensus (RANSAC) approach.
reconstruct fourier
Reconstruct a volume using Xmipp_reconstruct_fourier from a given set of particles. The alignment parameters will be converted to a Xmipp xmd file and used as direction projections to reconstruct.
reconstruct significant (Initial model)
This algorithm addresses the initial volume problem in SPA by setting it in a Weighted Least Squares framework and calculating the weights through a statistical approach based on the cumulative density function of different image similarity measures.
resolution 3D
Computes resolution by several methods
rotational spectra
Protocol to compute the rotational spectrum of the given particles.
rotational symmetry
Estimate the orientation of a rotational axis and symmetrize. The user should know the order of the axis (two-fold, three-fold, ...) If this is unknown you may try several and see the most consistent results.
screen deep learning
Protocol for screening particles using deep learning.
screen particles
Attach different merit values to every particle in order to prune the set. zScore evaluates the similarity of a particles with an average (lower zScore -> high similarity). SSNR evaluates the signal/noise ration in the Fourier space. Variance evaluates the varaince on the micrographs context where the particle was picked.
significant heterogeneity
3D Reconstruction with heterogeneous datasets
solid angles
Construct image groups based on the angular assignment. All images assigned within a solid angle are assigned to a class. Classes are not exclusive and an image may be assigned to multiple classes
split volume
Split volume in two
split volume hierarchical
Construct image groups based on the angular assignment. All images assigned within a solid angle are assigned to a class. Classes are not exclusive and an image may be assigned to multiple classes
structure mapping
A quantitive analysis of dissimilarities (distances) among the EM maps that placing the entire set of density maps in to a common space of comparison.The approach is based on statistical analysis of distance among elastically aligned EM maps, and results in visualizing those maps as points in a lower dimensional distance space.
subtract projection
Subtract volume projections from the experimental particles. The particles must have projection alignment in order to properly generate volume projections. An example of usage is to delete the virus capsid to refine only the genetic material.
swarm consensus
This is a 3D refinement protocol whose main input is a set of volumes and a set of particles. The set of particles has to be at full size (the finer sampling rate available), but the rest of inputs (reference volume and masks) can be at any downsampling factor. The protocol scales the input images and volumes to a size that depends on the target resolution. The input set of volumes is considered to be a swarm of volumes and they try to optimize the correlation between the volumes and the set of particles. This is an stochastic maximization and only a fraction of the particles are used to update the volumes and evaluate them.
tilt pairs particle picking (Picking)
Picks particles in a set of untilted-tilted pairs of micrographs.
trigger data
Waits until certain number of images is prepared and then send them to output. It can be done in 3 ways: - If *Send all particles to output?*' is _No_: Once the number of images is reached, a setOfImages is returned and the protocols finished (ending the streaming from this point). - If *Send all particles to output?*' is _Yes_ and: - If *Split particles to multiple sets?* is _Yes_: Multiple closed outputs will be returned as soon as the number of images is reached. - If *Split particles to multiple sets?* is _No_: Only one output is returned and it is growing up in batches of a certain number of images (completely in streaming).
validate overfitting
Check how the resolution changes with the number of projections used for 3D reconstruction. NOTE: Using the output plot, with the reconstruction of aligned gaussian noise, you can assess the validity of the reconstruction from your micrograph images. Practically, if the resolution of reconstruction based on your images is not considerably different from aligned gaussian noise one (for less number of particles),your images may not produce a valid reconstruction. This method has been proposed by: B. Heymann "Validation of 3D EM Reconstructions", 2015. (see References)
validate_nontilt
Ranks a set of volumes according to their alignment reliability obtained from a clusterability test.

Contributors: