Saravanan666/pypi-org huggingface dataset:
Package: scipion-em-cistem
This plugin provides wrappers for several programs ofcisTEMsoftware suite.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-cistemDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-cistem.gitinstallscipion installp -p /path/to/scipion-em-cistem --develcisTEM binaries will be installed automatically with the plugin, but you can also link an existing installation.Default installation path assumed issoftware/em/cistem-1.0.0-beta, if you want to change it, setCISTEM_HOMEinscipion.conffile pointing to the folder where the cisTEM is installed.It’s possible to use CTFFIND4 installed separately from cisTEM by definingCTFFIND4_HOMEvariable inscipion.conf. Setting this value will have the priority over Ctffind inside cisTEM.A complete list of tests can be seen by executingscipion test--show--grepcistemSupported versions1.0.0-beta (cistem)4.1.13, 4.1.14 (ctffind4)Protocolsctffind4import tomo CTFstilt-series ctffind4unblurfind particlesclassify 2DReferencesTimothy Grant and Alexis Rohou and Nikolaus Grigorieff. (2018) cisTEM, user-friendly software for single-particle image processing. eLife 7:e35383.
Package: scipion-em-cryoassess
This plugin provides a wrapper forCryoassesssoftware tools for automatic micrograph and 2D classes assessment.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-cryoassessDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-cryoassess.gitinstallscipion installp -p /path/to/scipion-em-cryoassess --develCryoassess software will be installed automatically with the plugin but you can also use an existing installation by providingCRYOASSESS_ENV_ACTIVATION(see below).
You also have to download training models separately (see below).Important:you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.Configuration variablesCONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the
PATH (not recommended), which can lead to execution problems mixing scipion
python with conda ones. One example of this could can be seen below but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”CRYOASSESS_ENV_ACTIVATION(default = conda activate cryoassess-1.0.0):
Command to activate the cryoassess environment.The deep-learning models can be downloaded fromauthors’ websiteand the folder with models is set with:CRYOASSESS_MODELS(default = software/em/cryoassess-models)VerifyingTo check the installation, simply run the following Scipion test:scipion test cryoassess.tests.test_protocols_cryoassess.TestCryoassessSupported versions1.0.0Protocolsassess micrographsassess 2D classesReferencesHigh-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines. Yilai Li, Jennifer N.Cash, John J.G. Tesmer, Michael A.Cianfrocco. Structure 2020, Volume 28 (7), Pages 858-869.e3
Package: scipion-em-cryocare
Scipion plugin for cryoCAREThis plugin allows to usecryoCARE-trains a denoising U-Net for tomographic reconstruction according to theNoise2Noisetraining paradigm- tomography methods into Scipion framework.InstallationThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:1. User (stable) version::scipion3 installp -p scipion-em-cryocare2. Developer (latest, may be unstable) version::Clone the source code repository:git clone https://github.com/scipion-em/scipion-em-cryocare.gitInstall:scipion3 installp -p local/path/to/scipion-em-cryocare --develProtocolsThe integrated protocols are:Load a previously trained model.Generate the training data.Training: uses two data-independent reconstructed tomograms to train a 3D cryoCARE network.4. Predict: generates the final restored tomogram by applying the cryoCARE trained network to both
even/odd tomograms followed by per-pixel averaging.TestsThe installation can be checked out running some tests. To list all of them, execute:scipion3 tests --grep cryocareTo run all of them, execute:scipion3 tests --grep cryocare --runTutorialThe test generates a cryoCARE workflow that can be used as a guide about how to use cryoCARE. The even/odd tomograms
required to use cryoCARE can be generated inside Scipion with:Pluginscipion-em-motioncorr: protocol “align tilt-series movies”.Pluginscipion-em-xmipptomo: protocol “tilt-series flexalign”.ReferencesCryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data.Tim-Oliver Buchholz et al., 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).Contact informationIf you experiment any problem, please contact us here:scipion-users@lists.sourceforge.netor open anissue.We’ll be pleased to help.Scipion Team
Package: scipion-em-cryodrgn
This plugin provides a wrapper forcryoDRGNsoftware: Deep Reconstructing Generative Networks for cryo-EM heterogeneous reconstruction.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-cryodrgnDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-cryodrgn.gitinstallscipion installp -p /path/to/scipion-em-cryodrgn --develcryoDRGN software will be installed automatically with the plugin but you can also use an existing installation by providingCRYODRGN_ENV_ACTIVATION(see below).Important:you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.Configuration variablesCONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the
PATH (not recommended), which can lead to execution problems mixing scipion
python with conda ones. One example of this could can be seen below but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”CRYODRGN_ENV_ACTIVATION(default = conda activate cryodrgn-3.1.0):
Command to activate the cryoDRGN environment.VerifyingTo check the installation, simply run the following Scipion test:scipion test cryodrgn.tests.test_protocols_cryodrgn.TestWorkflowCryoDrgnSupported versions2.1.0-beta, 2.3.0, 3.1.0-betaProtocolsanalyze resultspreprocess particlestraining VAEtraining ab initioReferencesUncovering structural ensembles from single particle cryo-EM data using cryoDRGN. Laurel Kinman, Barrett Powell, Ellen Zhong, Bonnie Berger, Joey Davis.https://www.biorxiv.org/content/10.1101/2022.08.09.503342v1CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks. Ellen D. Zhong, Tristan Bepler, Bonnie Berger, Joseph H. Davis. Nature Methods 18(2), 2021, 176-182. DOI 10.1038/s41592-020-01049-4Reconstructing continuous distributions of 3D protein structure from cryo-EM images. Ellen D. Zhong, Tristan Bepler, Joseph H. Davis, Bonnie Berger. ICLR 2020,https://arxiv.org/abs/1909.05215CryoDRGN2: Ab Initio Neural Reconstruction of 3D Protein Structures From Real Cryo-EM Images. Ellen D. Zhong, Adam Lerer, Joseph H. Davis, Bonnie Berger; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 4066-4075.https://openaccess.thecvf.com/content/ICCV2021/html/Zhong_CryoDRGN2_Ab_Initio_Neural_Reconstruction_of_3D_Protein_Structures_From_ICCV_2021_paper.html
Package: scipion-em-cryoef
This plugin provides a wrapper forcryoEFprogram.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-cryoefDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-cryoef.gitinstallscipion installp -p /path/to/scipion-em-cryoef --develCryoEF binaries will be installed automatically with the plugin, but you can also link an existing installation.
Default installation path assumed issoftware/em/cryoEF-1.1.0, if you want to change it, setCRYOEF_HOMEinscipion.conf`file to the folder where the cryoEF is installed. To check the installation, simply run the following Scipion test:scipion test cryoef.tests.test_protocols_cryoef.TestCryoEFSupported versions1.1.0Protocolsorientation analysisDetailed manual can be found insoftware/em/cryoEF-1.1.0/cryoEF_v1.1.0_manual.pdfReferences1.  Naydenova, K and Russo, CJ “Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy” Nature Communications (2017).
Package: scipion-em-deepfinder
Deepfinder plugin for ScipionDeepfinderprovides a deeplearning picking workflow for cryo-electron microscopy tomography data.InstallationThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:1. User (stable) version::scipion3 installp -p scipion-em-deepfinder2. Developer (latest, may be unstable) version::Clone the source code repository:git clone https://github.com/scipion-em/scipion-em-deepfinder.gitMove to devel branch:git checkout develInstall:scipion3 installp -p local/path/to/scipion-em-deepfinder --develConfiguration variablesCONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the
PATH (not recommended), which can lead to execution problems mixing Scipion
python with conda ones. One example of this can be seen below but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/anaconda/bin/conda shell.bash hook)”DF_ENV_ACTIVATION: (default = conda activate deepfinder-0.2):
Command to activate the DeepFinder environment.DF_HOME: (default = ScipionHome/Software/em/deepfinder-0.2):
Location of the DeepFinder package.ProtocolsThe integrated protocols are:Annotate: manual annotation of macromolecules in the tomograms, using a visual tool.Generate sphere targets: generates segmentation maps from annotations. These segmentation maps will be used as
targets to train DeepFinderTraining.Segment: segmentation of tomograms, using a trained neural network.Cluster: analyses the segmentation maps and outputs particle coordinates and class.Import DeepFinder coordinates.Import DeepFinder Training model.TestsThe installation can be checked out running some tests. To list all of them, execute:scipion3 tests --grep deepfinderTo run all of them, execute:scipion3 tests --grep deepfinder --runTo run a specific test, for example, the tests to check the sphere targets generation (the following command
can be copied from the test list displayed when listing the tests, as explained above):scipion3 tests deepfinder.tests.test_deepfinder.TestDeepFinderGenSphereTargetVideo tutorialsAplaylistwas created in I2PC Youtube channel to show how to use Deepfinder plugin in Scipion.ReferencesDeep Learning Improves Macromolecules Localization and Identification in 3D Cellular Cryo-Electron Tomograms.Emmanuel Moebel, Antonio Martinez-Sanchez et al., Nat Methods 18, 1386–1394 (2021).Contact informationIf you experiment any problem, please contact us here:scipion-users@lists.sourceforge.netor open anissue.We’ll be pleased to help.Scipion Team
Package: scipion-em-dynamo
Scipion plugin for DynamoThis plugin allows to useDynamo- an environment for subtomogram averaging cryo-ET data - within the Scipion framework.InstallationThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:1. User (stable) version::scipion3 installp -p scipion-em-dynamo2. Developer (latest, may be unstable) version::Clone the source code repository:git clone https://github.com/scipion-em/scipion-em-dynamo.gitMove to devel branch:git checkout develInstall:scipion3 installp -p local/path/to/scipion-em-dynamo --develProtocolsThe integrated protocols are:bin tomograms: Reduce the size of a set of tomograms by a binning factor.vectorial picking: Manual vectorial picking using Dynamo dtmslice GUI.subtomogram extraction: Extraction of subtomograms.import subtomograms from Dynamo .tbl files.model workflow: apply a geometry model to a set of meshes, normally the result of the vectorial picking protocol.subtomogram alignment.TestsThe installation can be checked out running some tests. To list all of them, execute:scipion3 tests --grep dynamoTo run all of them, execute:scipion3 tests --grep dynamo --runTo run a specific test, for example, the tests to check the protocol for averaging subtomograms (the following command
can be copied from the test list displayed when listing the tests, as explained above):scipion3 tests dynamo.tests.test_dynamo_average_subtomos.TestDynamoAverageSubtomogramsTutorialA tutorial with examples about how to use Dynamo within Scipion can be foundhere.ReferencesDynamo: A flexible, user-friendly development tool for subtomogram averaging of cryo-EM data in high-performance computing environments.Daniel Castaño-Díez et al., Journal of Structural Biology, 2012.Contact informationIf you experiment any problem, please contact us here:scipion-users@lists.sourceforge.netor open anissue.We’ll be pleased to help.Scipion Team
Package: scipion-em-eman2
This plugin provides wrappers around several programs ofEMANsoftware suite.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-eman2Developer’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-eman2.gitinstallscipion installp -p /path/to/scipion-em-eman2 --develEMAN software will be installed automatically with the plugin but you can also use an existing installation by providingEMAN_ENV_ACTIVATION(see below).Important:you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.Configuration variablesCONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the
PATH (not recommended), which can lead to execution problems mixing scipion
python with conda ones. One example of this could can be seen below but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”EMAN_ENV_ACTIVATION(default = conda activate eman-2.99.52):
Command to activate the EMAN environment.The default scratch directory is assumed/tmp/. You can change it by settingEMAN2SCRATCHDIRinscipion.confor your shell environment.To check the installation, simply run one of the following Scipion tests:scipion test eman2.tests.test_protocols_eman.TestEmanTiltValidate
scipion test eman2.tests.test_protocols_eman.TestEmanRefineEasy
scipion test eman2.tests.test_protocols_eman.TestEmanRefine2DBispec
scipion test eman2.tests.test_protocols_eman.TestEmanRefine2D
scipion test eman2.tests.test_protocols_eman.TestEmanReconstruct
scipion test eman2.tests.test_protocols_eman.TestEmanInitialModelMda
scipion test eman2.tests.test_protocols_eman.TestEmanInitialModelGroel
scipion test eman2.tests.test_protocols_eman.TestEmanInitialModelSGD
scipion test eman2.tests.test_protocols_eman.TestEmanCtfAuto
scipion test eman2.tests.test_protocols_eman.TestEmanAutopickA complete list of tests can also be seen by executingscipion test--show--grepemanSupported versions2.99.47, 2.99.52Protocolsboxerboxer autoctf autoinitial modelinitial model SGDreconstructrefine 2drefine 2d bispecrefine easytilt validateReferencesG. 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
Package: scipion-em-emantomo
Scipion plugin for EMAN2 TomographyThis plugin provide wrappers around several programs ofEMAN2tomography software suite.InstallationThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:1. User (stable) version::scipion3 installp -p scipion-em-emantomo2. Developer (latest, may be unstable) version::Clone the source code repository:git clone https://github.com/scipion-em/scipion-em-emantomo.gitMove to devel branch:git checkout develInstall:scipion3 installp -p local/path/to/scipion-em-emantomo --develProtocolsThe integrated protocols are:Tilt series alignment and tomograms reconstruction.CTF estimation.Tomogram clipping.Subtomograms manual picking.Template matching picking.Average subtomograms.Subtomograms extraction from the tomograms.Subtomograms extraction from the tilt series.Initial model.New initial model (from particles extracted from the tilt series).Subtomograms refinement.New subtomograms refinement (from particles extracted from the tilt series).New multi-reference classification of subtomograms (from particles extracted from the tilt series).TestsThe installation can be checked out running some tests. To list all of them, execute:scipion3 tests --grep emantomoTo run all of them, execute:scipion3 tests --grep emantomo --runTo run a specific test, for example, the tests to check the protocol for averaging subtomograms (the following command
can be copied from the test list displayed when listing the tests, as explained above):scipion3 tests emantomo.tests.test_protocols_sta_classic_workflow.TestEmanTomoAverageSubtomogramsStaClassicTutorialThe workflow test generates a emantomo workflow that offers an overview of how to use emantomo.scipion3 tests emantomo.tests.test_protocols_sta_classic_workflowReferencesSingle particle tomography in EMAN2.Jesús G. Galaz-Montoya et al., Journal of Structural Biology, 2015.High resolution single particle refinement in EMAN2.1.James M. Bell et al., Methods, 2016.Contact informationIf you experiment any problem, please contact us here:scipion-users@lists.sourceforge.netor open anissue.We’ll be pleased to help.Scipion Team
Package: scipion-em-embuild
EMBuild pluginEMBuild: Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly.Installing the pluginIn order to install the plugin follow these instructions:Install the pluginscipion installp -p scipion-em-embuildor through theplugin managerby launching Scipion and followingConfiguration>>PluginsTo install in development modeClone or download the plugin repositorygit clone https://github.com/scipion-em/scipion-em-embuild.gitInstall the plugin in developer mode.scipion installp -p local/path/to/scipion-em-embuild --develBuildbot statusStatus devel version:Status production version:
Package: scipion-em-empiar
Scipion Empiar DepositorThis project is a Scipion plugin to make depositions tohttps://www.ebi.ac.uk/pdbe/emdb/empiarSetupIn order to install the plugin follow these instructions:Install this plugin:scipion installp -p scipion-em-empiaror through theplugin managerby launching Scipion and followingConfiguration>>PluginsAlternatively, in devel mode:git clone https://github.com/scipion-em/scipion-em-empiar.git
scipion installp -p local/path/to/scipion-em-empiar --develDownload Aspera Connect:Go tohttps://www.ibm.com/aspera/connect/and download the latest version.Register an account in the EMPIAR deposition and Segmentation Annotation ToolGo tohttps://www.ebi.ac.uk/pdbe/emdb/empiar/deposition/register/and get an API token atGet empiar-deposition API tokensectionOpen scipion’s config file ‘scipion3 config –show’ and add the following variables:ASCP = <aspera_binary_path> (usually it is located at $HOME/.aspera/connect/bin/ascp)
ASPERA_SCP_PASS= <aspera_shares_user_password>
EMPIAR_TOKEN = <empiar_token>
Package: scipion-em-emready
EMReady: Improvement of cryo-EM maps by simultaneous local and non-local deep learning.InstallationYou will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-emreadyor through theplugin managerby launching Scipion and followingConfiguration>>PluginsDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-emready.gitinstallscipion installp -p /path/to/scipion-em-emready --develEMReady software will be installed automatically with the plugin but you can also use an existing installation by providingEMREADY_ENV_ACTIVATIONandEMREADY_HOME(see below).Important:you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.Configuration variablesCONDA_ACTIVATION_CMD: If undefined, it will rely on conda command being in the
PATH (not recommended), which can lead to execution problems mixing scipion
python with conda ones. One example of this could can be seen below but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”EMREADY_ENV_ACTIVATION(default = conda activate emready-1.0):
Command to activate the EMReady environment.EMREADY_HOME(default = software/em/emready-1.0):
Path with EMReady source code.VerifyingTo check the installation, simply run the following Scipion test:scipion test emready.tests.test_protocol_sharpening.TestEMReadySharpeningSupported versions1.0ProtocolssharpeningReferencesHe J, Li T, Huang S-Y. Improvement of cryo-EM maps by simultaneous local and non-local deep learning. Nature Communications, 2023; 14:3217.
Package: scipion-em-emxlib
EMXlib pluginThis plugin allows to import metadata to and from EMX formatElectron Microscopy eXchange (EMX) initiative was launched at the 2012 Instruct
Image Processing Center Developer Workshop with the intention of developing a
first set of standard conventions for the interchange of information for
single-particle analysis
(seeURLandhttps://www.ncbi.nlm.nih.gov/pubmed/26873784for details).Install this pluginYou will need to use3.0.0version of Scipion to run these protocols.Stable versionscipion installp -p scipion-em-emxlibORthrough the plugin manager GUI by launching Scipion and followingConfiguration>>PluginsDeveloper’s versionDownload repository:git clone https://github.com/scipion-em/scipion-em-emxlib.gitInstall:scipion installp -p path_to_scipion-em-emxlib --develBinary filesNo binary files are needed.TestsTo check the installation, simply run the following Scipion tests:scipion test emxlib.tests.test_workflow_emx.TestEmxWebscipion test emxlib.tests.test_protocols_emx.TestEmxBasescipion test emxlib.tests.test_protocols_export_particles.TestExportParticlesEMXProtocolsemx export: export particles, micrograph, CTFs, etc to EMX formatgeneral import (particles, micrographs, etc) allow metadata information to be encoded using EMX conventionsExamplesSeeURLBuildbot statusStatus devel version:Status production version:
Package: scipion-em-facilities
stable:devel:‘scipion-em-facilities’ plugin allows to use different utils for cryo-EM facilities
(like monitors) within the Scipion framework.Monitors are used to produce live analysis plots, generate reports or
raise alerts when some problems are detected. A monitor example is the CTF-monitor,
that checks the computed defocus values for each micrograph as they are generated.
CTF-monitor may raise an alert if the defocus values are above or below certain thresholds.
A special case of this monitors is the monitor summary which encapsulates the CTF Monitor,
the system monitor and the movie gain monitor and continuously creates a report.This module contains protocols and utilities related with monitors.Please, check thefacilities documentationfor more details.InstallationYou will need to useScipion 3.0to be able to run these protocols. If you want to use the summary monitor with grafana
you will need to create the file secrets.cfg in the directory defined by the variable EMFACILITIES_HOME
(see the above mention web site for details).To install the plugin, you have two options:Stable versionscipion3 installp -p scipion-em-facilitiesDeveloper’s version1st. Download repositorygit clone https://github.com/scipion-em/scipion-em-facilities.git /path/to/scipion-em-facilities2nd. Install the pluginscipion3 installp -p /path/to/scipion-em-facilities --develTestingTo check the installation, simply run the following Scipion test:scipion3 test --grep emfacilities --mode modules --runIf--runis not passed, it only shows the available tests to check.