Saravanan666/pypi-org huggingface dataset:
Package: scipion-em-nysbc
This plugin provide a wrapper around3DFSCprogram developed at Salk Institute and NYSBC.InstallationYou will need to use2.0version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-nysbcDeveloper’s versiondownload repositorygit clone https://github.com/scipion-em/scipion-em-nysbc.gitinstallscipion installp -p path_to_scipion-em-nysbc --devel3DFSC binaries will be installed automatically with the plugin atsoftware/em/nysbc3DFSC-2.5, but you can also link an existing installation.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 bellow but
depending on your conda version and shell you will need something different:
CONDA_ACTIVATION_CMD = eval “$(/extra/miniconda3/bin/conda shell.bash hook)”NYSBC_3DFSC_HOME(default = software/em/nysbc3DFSC-2.5):
Path  where the 3DFSC is installed.NYSBC_3DFSC_ACTIVATION_CMD(default = conda activate fsc):
Command to  activate the 3DFSC environment.VerifyingTo check the installation, simply run the following Scipion test:scipion test nysbc.tests.test_protocols_nysbc.TestNysbc3DFSCSupported versions2.5, 3.0Protocols3d fscReferencesYong Zi Tan, Philip R Baldwin, Joseph H Davis, James R Williamson, Clinton S Potter, Bridget Carragher & Dmitry Lyumkis. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nature Methods volume 14, pages 793–796 (2017).
Package: scipion-em-powerfit
Powerfit scipion pluginProgram from Alexandre Bonvin and Gydo van Zundert (Utrecht University) for rigid body fitting of an atomic structure into a 3D volume. SeePowerfit home pagefor details).Install this pluginYou will need to use2.0.0version of Scipion to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-powerfitORthrough the plugin manager GUI by launching Scipion and followingConfiguration>>PluginsDeveloper’s versionDownload repository:git clone https://github.com/scipion-em/scipion-em-powerfit.gitInstall:scipion installp -p path_to_scipion-em-powerfit --develBinary filesPowerfit binary file is installed with the plugin.TestsTested with Powerfit version: 2.0.To check the installation, simply run the following Scipion test:scipion test powerfit_scipion.tests.test_powerfitSupported versions of Powerfit2.0Protocolspowerfit-scipion:Powerfitprogram functionality.ExamplesSeeModel Building TutorialAdditionally,hereyou have theTutorialfrom the original developer.Buildbot statusStatus devel version:Status production version:
Package: scipion-em-pwperformance
pwperformanceis a Scipion plugin with tests to measure performance and send benchmarks to a Codespeed serverPlugin installationgit clone https://github.com/scipion-em/scipion-em-pwperformance.git
scipion3 installp -p /path/to/scipion-em-pwperformance --develEnvironment variablesDefine the following environment vars:CODESPEED_URL = Codespeed server URL to send benchmarks to. Defaults to "http://localhost:8000"
CODESPEED_ENV = Environment name. Environment describes your testing PC configuration. Defaults to "unknown"
CODESPEED_PROJECT = This should be the plugin you want to test. Defaults to "pyworkflow"
CODESPEED_BRANCH = Git branch of your project. Defaults to "devel"
CODESPEED_COMMIT = Git commit id of your project. Defaults to "1"Codespeed server installationconda create -y -n codespeed python=3.6conda activate codespeedpip3 install pypandoc==1.7.5 setuptools==57.5.0 gunicorngit clonehttps://github.com/tobami/codespeedcd codespeedpip3 install -e .pip3 install “django<2.2,>=1.11”python manage.py migratepython manage.py createsuperuserpython manage.py runserver 8000Go tohttp://localhost:8000/admincreate an environment (your CODESPEED_ENV)create a Github-type project (name = CODESPEED_PROJECT) with a correct url (e.g.https://github.com/scipion-em/scipion-pyworkflow), branch (e.g. “devel” or your own CODESPEED_BRANCH) and tick “Track changes”create a “devel” (or your own CODESPEED_BRANCH) branchExample runRun any of the following plugin tests to save the data on the codespeed server, e.g.:scipion3 tests pwperformance.tests.test_profiling_load.TestProfilingLoadGUI
scipion3 tests pwperformance.tests.test_set_performance.TestSetPerformanceSteps
scipion3 tests pwperformance.tests.test_exportsteps.TestExportSteps
Package: scipion-em-pyseg
Scipion plugin for PySegThis plugin allows to usePySeg- De novo analysis for cryo-electron tomography - within the Scipion framework.SetupSystem pre-requisites:Cmake 2.6.3+. The intallation command in Ubuntu is:sudo apt-get install cmakeGSL (GNU Scientific Library). In Ubuntu, the installation command is:sudo apt-get install libgsl-devgcc/g++ version greater or equal to 5 (forDisPerSEcompilation).InstallationThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:1. User (stable) version::scipion3 installp -p scipion-em-pyseg2. Developer (latest, may be unstable) version::Clone the source code repository:git clone https://github.com/scipion-em/scipion-em-pyseg.gitInstall:scipion3 installp -p local/path/to/scipion-em-pyseg --develProtocolsThe integrated protocols are:pyseg - fils: Filters a MbGraphMCF (Mean Cumulative Function) object by extracting a filament networkpyseg - graphs: Analyzes a GraphMCF (Mean Cumulative Function) from a segmented membranepyseg - picking: Extracts particles from a filament network of a oriented single membrane graphpyseg - 2D classification: Unsupervised and deterministic classification of membrane-bound particlespyseg - posrec: post-process already reconstructed particles; rot angle randomization and membrane suppressionpyseg - preseg membranes: Segment membranes into membranes, inner surroundings and outer surroundingsTestsThe installation can be checked out running some tests (Important: TestPosRec requires the pluginsscipion-em-xmippandscipion-em-reliontomoto be installed:scipion3 tests pyseg.tests.test_preseg_graphs_fils_picking.TestFromPresegToPickingscipion3 tests pyseg.tests.test_pos_rec.TestPostRecTutorialA tutorial about how to use PySeg within Scipion can be foundhere.ReferencesTemplate-free detection and classification of heterogeneous membrane-bound complexes in cryo-electron tomograms.A. Martinez-Sanchez et al., Nature Methods, 2020.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-reliontomo
This plugin provide wrappers around several programs ofRELIONsoftware suite (version 3.0) for its use in Tomography.Current developmentThis plugin is currently inBETAmode.InstallationYou will need to use3.0version of Scipion to be able to run these protocols.ProtocolsExtract coordinates from pseudo-subtomograms: Protocol to extract a set of 3D coordinates from a set of pseudo-subtomograms.Import coordinates 3D from a star file: Protocol to import a set of 3D coordinates from a star file.Import subtomograms from a star file: Protocol to import a set of subtomograms from a star file.3D Classification of subtomograms: 3D Classification of subtomograms.Tomo CTF refine: Tomo CTF refineDe novo 3D initial model: Generate a de novo 3D initial model from the pseudo-subtomograms.Apply operation to Relion particles: Operate on the particles star file.Make pseudo-subtomograms: Make pseudo-subtomograms.Sharpen a 3D reference maps: Sharpen a 3D reference map and estimate the gold-standard FSC curves for subtomogram averaging.Prepare data for Relion 4: Prepare data for Relion 4Reconstruct particle from tilt series:  Reconstruct particle from the original tilt series images.Auto-refinement of subtomograms:  Auto-refinement of subtomograms.Rec. particle averaging subtomograms: 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.Tomo frame align: Tomo frame alignReconstruct tomograms from prepare data prot: This protocol reconstructs a single tomogram using Relion. It is very useful  to check if the protocol “Prepare data” has been applied correctly (in terms of flip  options, for example).Matching coordinates: Protocol to generate a set of pseudosubtomograms taking into account the intersection of  a set of 3D coordinates and a set of pseudosubtomograms as input.Latest plugin versionsIf you want to check the latest version and release history go toCHANGESInstalling the pluginIn order to install the plugin follow these instructions:scipion installp -p scipion-em-reliontomoor 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-reliontomo.gitInstall the plugin in developer mode.scipion installp -p local/path/to/scipion-em-reliontomo --develTo check the installation, simply run one of the tests. A complete list of tests can be displayed by executingscipion3 tests--grepreliontomo--showSupported versionsRelion 3.0, 4.0ReferencesScheres et al., JMB, 2012Scheres et al., JSB, 2012Kimanius et al., eLife, 2016Zivanov et al., eLife, 2018Buildbot statusStatus devel version:Status production version:
Package: scipion-em-repic
REliable PIcking by Consensus (REPIC) provides a picking consensus approach for cryoelectron microscopy data.Given several set of coordinates picked by several picker, REPIC will determine the consensus set of particles. It means the subset of most reliable particles.InstallationInstall this plugin in devel mode:Using the command line:scipion3 installp -p yourpathtoinstall/scipion-em-repic --develReferenceSee the preprint in: [https://www.biorxiv.org/content/10.1101/2023.05.13.540636v1]
Package: scipion-em-resmap
This plugin provides a wrapper forResMap program.InstallationYou will need to use3.0version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable versionscipion installp -p scipion-em-resmapDeveloper’s versiondownload repositorygit clone https://github.com/scipion-em/scipion-em-resmap.gitinstallscipion installp -p path_to_scipion-em-resmap --develResMap binaries will be installed automatically with the plugin, but you can also link an existing installation.
Default installation path assumed issoftware/em/resmap-1.95, if you want to change it, setRESMAP_HOMEinscipion.conffile pointing to the folder where the ResMap is installed. ResMap binary (default ResMap-1.95-cuda-Centos7x64) and CUDA lib module (default ResMap_krnl-cuda-V8.0.61-sm60_gpu.so) can be set byRESMAPandRESMAP_GPU_LIBvars, respectively.
You also might need to setRESMAP_CUDA_LIBin the config file pointing to the correct location of system CUDA libraries.To check the installation, simply run the following Scipion test:scipion test resmap.tests.test_protocols_resmap.TestResMapA complete list of tests can also be seen by executingscipion test--show--grepresmapSupported versions1.95Protocolslocal resolutionReferencesKucukelbir A. et al. (2014) Quantifying the local resolution of cryo-EM density maps. Nature Methods 11, 63-65.
Package: scipion-em-sidesplitter
This plugin provides a wrapper forSIDESPLITTERprogram for mitigating local overfitting.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-sidesplitterDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-sidesplitter.gitinstallscipion installp -p /path/to/scipion-em-sidesplitter --develSIDESPLITTER sources will be installed automatically with the plugin, but you can also link an existing installation.Default installation path assumed issoftware/em/sidesplitter-1.2, if you want to change it, setSIDESPLITTER_HOMEinscipion.conffile pointing to the folder where the SIDESPLITTER is installed.To check the installation, simply run one of the following Scipion tests:scipion test sidesplitter.tests.test_protocol_sidesplitter.TestSideSplitterA complete list of tests can also be seen by executingscipion test--show--grepsidesplitterSupported versions1.2Protocolslocal filterReferencesKailash Ramlaul, Colin M. Palmer and Christopher H. S. Aylett (2020). Mitigating Local Over-fitting During Single Particle Reconstruction with SIDESPLITTER.https://www.biorxiv.org/content/10.1101/2019.12.12.874081v2
Package: scipion-em-simple
Simple pluginThis plugin allows to use Simple programs within the Scipion framework.Simple is a a program package for cryo-EM image processing, focusing on ab initio 3D reconstruction of low-symmetry single-particles. It is developed by [Hans Elmlund](http://simplecryoem.com).Supported versions of Simple: 2.1DependenciesWe need libgfortran3sudo apt install libgfortran3SetupInstall this plugin:scipion installp -p scipion-em-simpleORthrough the plugin manager GUI by launching Scipion and followingConfiguration>>PluginsAlternatively, in devel mode:scipion installp -p local/path/to/scipion-em-simple --devel![build status](http://heisenberg.cnb.csic.es:9980/badges/simple_devel.svg)
Package: scipion-em-sll
Scipion plugin for CryoEM tools developed atSciLifeLab.InstallationYou will need to useScipion 2.0to be able to run these protocols. To install the plugin, you have two options:Stable versionscipioninstallp-pscipion-em-sllDeveloper’s versiondownload repositorygitclonehttps://github.com/scipion-em/scipion-em-sll.gitinstallscipioninstallp-ppath_to_scipion-em-sll--develTo check the installation, simply run one of the following Scipion tests:scipiontestgctf.tests.test_protocols_gctf.TestGctfRefinescipiontestgctf.tests.test_protocols_gctf.TestGctfProtocolsProtocolDescriptionfilter classes CCSimple protocol to select ‘good’ classes based on cross-correlation and the number of particles assigned.filter CTFIf we took the bones out, it wouldn’t be crunchy, now would it?ReferencesNone yet
Package: scipion-em-smartscope
Plugin to manage the interaction with the SmartScope framework.InstallationYou will need to installSmartscopeprevious the plugin installationFollow the steps to installit with Docker
(Installation with Anaconda/Miniconda is not abailable yet)
Developer’s version:Download repositorygit clone -b devel https://github.com/scipion-em/scipion-em-smartscope.gitInstallscipion installp -p /path/to/scipion-em-smartscope --develConfigurationSmartscope provide a token when the installation finish and you are logged,visit herefor more details. Please add the token in the scipion.conf file asSMARTSCOPE_TOKEN= …XXXfeb270a1bc4120b1XXXX…Smartscope will save the data (not the acquisition managed by SerialEM) in the path you decided in the installation procedure. Please, provide that information on the scipion.conf asSMARTSCOPE_DATA_SESSION_PATH= path/smartscope/save/dataAdd the url to acces to the Smartscope web, by default ishttp://localhost:48000/but if you change the url or the port please add the new url in the scipion.conf asSMARTSCOPE_LOCALHOST=http://localhost:48000/Once you edit the scipion.conf please save it and runscipion configProtocolsSmartscope connectionProvide calculationsSmartscope feedback
Package: scipion-em-sphire
This plugin provides a wrapper for some programs ofSPHIREsoftware suite:JANNI (Just Another Noise 2 Noise Implementation): a neural network denoising toolcrYOLO: a fast and accurate particle picking procedure. It’s based on convolutional neural networks and utilizes the popular You Only Look Once (YOLO) object detection system.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 versionIt can be installed in user mode via Scipion plugin manager (Configuration>Plugins) or using the command line:scipion installp -p scipion-em-sphireDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-sphire.gitinstallscipion installp -p /path/to/scipion-em-sphire --develcrYOLO software will be installed automatically with the plugin but you can also use an existing installation by providingCRYOLO_ENV_ACTIVATION(see below).Important:you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.To check the installation you can run the plugin’s tests:scipion test--grepsphire--runConfiguration 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)”CRYOLO_ENV_ACTIVATION(default = conda activate cryolo-1.9.7):
Command to activate the crYOLO environment.NAPARI_ENV_ACTIVATION(default = conda activate napari-0.4.17):
Command to activate napari environment (used only for tomo picker viewer).Downloaded crYOLO and JANNI general models can be found in the following locations:<SCIPION_HOME>/software/em/cryolo_model-[model_version]<SCIPION_HOME>/software/em/cryolo_negstain_model-[model_version](not installed by default)<SCIPION_HOME>/software/em/janni_model-[model_version]Running on CPUcrYOLO can run on CPU, however this is only recommended for picking protocol and not training.
For that reason the CPU implementation is only available for thecrYOLO-Picking protocol.The CPU implementation of crYOLOis not installed by default. Therefore you must install thecryoloCPU-[version]package in theConfiguration>Plugins>>scipion-em-sphireor by running:scipion installb cryoloCPUThe CPU version of crYOLO is installed under a separate conda environment calledcryoloCPU-[version]. If you already have a cryoloCPU environment pre-installed, then modify the following variable in the Scipion config file:CRYOLO_ENV_ACTIVATION_CPU = conda activate envNameSupported versions1.8.5, 1.9.3, 1.9.6, ,1.9.7Protocolsimport crYOLO training modelcrYOLO pickingcrYOLO tomo pickingcrYOLO trainingJANNI denoisingReferencesWagner, T. et al. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Communications Biology 2, (2019).
Package: scipion-em-spider
This plugin provides wrappers for several programs ofSPIDERsoftware 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-spiderDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-spider.gitinstallscipion installp -p /path/to/scipion-em-spider --develSPIDER binaries will be installed automatically with the plugin, but you can also link an existing installation.
Default installation path assumed issoftware/em/spider-26.06, if you want to change it, setSPIDER_HOMEinscipion.conffile to the folder where the SPIDER is installed. Additional information about using SPIDER with MPI can be found on a separatepage. Unfortunately, at the moment we do not support MPI in our SPIDER wrappers, since it requires a lot of effort to refactor almost all protocols. :(
Depending on you CPU type you might want to change the default binary fromspider_linux_mp_intel64to a different one by explicitly settingSPIDERvariable.To check the installation, simply run one of the following Scipion tests:scipion test spider.tests.test_protocols_spider_reconstruct.TestSpiderReconstruct
scipion test spider.tests.test_protocols_spider_align.TestSpiderAlign
scipion test spider.tests.test_workflow_spiderMDA.TestSpiderWorkflow
scipion test spider.tests.test_workflow_spiderMDA.TestSpiderConvert
scipion test spider.tests.test_protocols_spider_projmatch.TestSpiderRefinementA complete list of tests can also be seen by executingscipion test--show--grepspiderSupported versions26.06ProtocolsAlign AP SRAlign pairwiseCA PCAClassification protocols: Diday, K-means, WardCustom 2D maskFilter particlesReconstruct FourierRefinementReferencesJ. Frank et al. (1996). SPIDER and WEB: Processing and visualization of images in 3D electron microscopy and related fields. JSB. 116: 190-199.
Package: scipion-em-spoc
This plugin provide wrappers around several programs ofSPOC.stable:devel: |InstallationYou will need to use3.0version of Scipion to be able to run these protocols. To install the plugin, you have two options:Stable version (not avalaible yet)scipion installp -p scipion-em-spocDeveloper’s versiondownload repositorygit clone https://github.com/scipion-em/scipion-em-spoc.gitinstallscipion installp -p path_to_scipion-em-spoc --develSPOC binaries will be installed automatically with the plugin.Default installation path assumed issoftware/em/spoc-1.0, if you want to change it, setSPOC_HOMEinscipion.conffile pointing to the folder where the SPOC is installed.To check the installation, simply run one of the following Scipion tests:scipion3 tests spoc.tests.test_protocols_spoc.TestFscFdrControlA complete list of tests can also be seen by executingscipion test--show--grepspocSupported versions1.0ProtocolsFSC_FDR ControlReferencesBeckers, M., Jakobi, A. J., Sachse, C. (2019) Thresholding of cryo-EM density maps by false discovery rate control. IUCr Journal 6 (1)
Package: scipion-em-susantomo
This plugin provides wrappers forSusansoftware: subtomogram averaging (StA) workflow for CryoET based on sub-stacks of images instead of sub-volumes of tomograms.
SUSAN uses substacks that are cropped on-the-fly from the aligned tilt-series stack and performs the CTF correction according to the selected operation (alignment or reconstruction). With this approach we decrease the
computational resources needed in a typical subtomogram averaging pipeline, as we no longer need the CTF corrected stacks, the full tomogram reconstructions, or all the subtomograms in multiple binning
stages.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-susantomoDeveloper’s versiondownload repositorygit clone -b devel https://github.com/scipion-em/scipion-em-susantomo.gitinstallscipion installp -p /path/to/scipion-em-susantomo --develSUSAN sources will be downloaded and compiled automatically with the plugin, but you can also link an existing installation. Default installation path assumed issoftware/em/susan-0.1, if you want to change it, setSUSAN_HOMEinscipion.conffile to the folder where the SUSAN is installed.SUSAN installation requires CUDA libraries, gcc >= 9.x and cmake 3.22.x. OpenMPI is optional amd only required for running SUSAN on more than one cluster node. MATLAB is not required as this plugin uses Python API.If you need to use CUDA different from the one used during Scipion installation (defined byCUDA_LIB), you can addSUSAN_CUDA_LIBvariable to the config file.If you have to use a MPI for SUSAN different from Scipion MPI, you can setSUSAN_MPI_BINandSUSAN_MPI_LIBvariables in the config file. At the moment MPI support in the plugin is not working.VerifyingTo check the installation, simply run one of the tests. A complete list of tests can be displayed by executingscipion test--show--grepsusantomoSupported versions0.1Protocolsctf estimationmulti-reference alignmentaverage and reconstructcreate a subsetReferencesSánchez RM, Mester R, Kudryashev M. Fast Cross Correlation for Limited Angle Tomographic Data. In: Felsberg M., Forssén PE., Sintorn IM., Unger J. (eds) Image Analysis. SCIA 2019. Lecture Notes in Computer Science, vol 11482. Doi: 10.1007/978-3-030-20205-7_34R.M. Sánchez, R. Mester and M. Kudryashev. Fast Alignment of Limited Angle Tomograms by projected Cross Correlation. 2019 27th European Signal Processing Conference (EUSIPCO), 2019, pp. 1-5, doi: 10.23919/EUSIPCO.2019.8903041