The Docker image for the latest stable release (May2020) is now available.
Why did we do this?
Docker is a very popular container platform which can be run on a multitude of platforms (UNIX, MAC, Windows), on laptops, desktops or even on cloud instances. Given the complexity of some of the Neuroconductor packages and taking into account that some of them are not yet compatible with the Windows platform, we've decided to provide all of our users with an already set up Neuroconductor Docker image that contains the required system dependencies as well as all the Neuroconductor Packages. Our goal was to alleviate the pain of having to setup all the system requirements and packages while at the same time ensuring that we offer a stable solution for conducting reproducible research. This image is based on our most recent release and we will continue to update it as we push new releases.
Use Instructions
- To download the image Docker client needs to be installed locally. Clients for Mac, UNIX and Windows can be found at https://docs.docker.com/get-docker/. Installation is straight forward and should not take too long.
- Once the Docker client is installed the next step is to open a terminal window. Please use this guide if you are not sure how to do so.
- Next step is to pull the Neuroconductor Docker image locally. This can be accomplished from the terminal window please use the following command (you can copy paste it from here)
docker pull adigherman/neuroconductor-release - Once the image was downloaded you can connect to it by running the following command:
docker run -it adigherman/neuroconductor-release /bin/bash
Image Specs:
| aal | 0.1.1 | Automated Anatomical Labeling (AAL) Atlas |
| afnir | 0.4.6 | Wrapper Functions for AFNI (Analysis of FunctionalNeuroImages) |
| alvin | 0.3.0 | ALVIN Ventricle Atlas |
| ANTsR | 0.5.6.0.0 | ANTs in R: Quantification Tools for Biomedical Images |
| ANTsRCore | 0.7.4 | Core Software Infrastructure for ANTsR |
| aws | 2.4.1 | Adaptive Weights Smoothing |
| bftools | 0.2.2 | BioFormats Tools |
| brainKCCA | 0.1.0 | Region-Level Connectivity Network Construction via Kernel Canonical Correlation Analysis |
| brainR | 1.6.0 | Helper Functions to 'misc3d' and 'rgl' Packages for Brain Imaging |
| cap | 0.1.0 | Covariate Assisted Principal (CAP) Regression for CovarianceMatrix Outcomes |
| cfma | 1.0.1 | Causal Functional Mediation Analysis |
| cifti | 0.4.6.0 | Toolbox for Connectivity Informatics Technology Initiative(CIFTI) Files |
| clever | 0.1.5 | Calculate Leverage of Component Models |
| dcemriS4 | 0.57.2 | A Package for Image Analysis of DCE-MRI (S4 Implementation) |
| dcm2niir | 0.6.9.1 | Conversion of DICOM to NIfTI Imaging Files Through R |
| dcmsort | 0.3.0 | Sort DICOM Images |
| dcmtk | 0.6.8.1 | Wrapper for DICOM Toolkit (DCMTK) |
| DensParcorr | 1 | Dens-Based Method for Partial Correlation Estimation in LargeScale Brain Networks |
| divest | 0.8.2 | Get Images Out of DICOM Format Quickly |
| dti | 1.5.1 | Analysis of Diffusion Weighted Imaging (DWI) Data |
| eegUtils | 0.3.0.9000 | A collection of utilities for EEG analysis |
| EveTemplate | 1.0.0 | JHU-MNI-ss (Eve) template |
| extrantsr | 3.9.13 | Extra Functions to Build on the ANTsR Package |
| flexconn | 0.5.4.5 | FLEXCONN Model |
| fmri | 1.9.3 | Analysis of fMRI Experiments |
| fmriqa | 0.4.0 | Functional MRI Quality Assurance Routines |
| freesurfer | 1.6.5 | Wrapper Functions for Freesurfer |
| fslr | 2.24.4 | Wrapper Functions for FSL (FMRIB Software Library) fromFunctional MRI of the Brain (FMRIB) |
| gganatogram | 1.1.1 | Create Anatograms of Various Species |
| ggBrain | 0.1 | ggplot Brain Images |
| ggneuro | 0.5.0 | Plotting Functions for Neuroimaging Data in ggplot2 |
| ggseg | 1.5.3 | Plotting tool for brain atlases |
| gifti | 0.7.5.9001 | Reads in Neuroimaging GIFTI Files with Geometry Information |
| I2C2 | 0.2.4 | Image Intraclass Correlation Coefficient |
| ichseg | 0.17.1 | Intracerebral Hemorrhage Segmentation of X-Ray ComputedTomography (CT) Images |
| ITKR | 0.5.3 | ITK in R |
| itksnapr | 2.1 | Package of ITK-SNAP |
| kirby21.asl | 1.7.0 | Example ASL Data from the Multi-Modal MRI ReproducibilityResource |
| kirby21.base | 1.7.2.1 | Example Data from the Multi-Modal MRI Reproducibility Resource |
| kirby21.det2 | 1.7.0 | Example DET2 Structural Data from the Multi-Modal MRIReproducibility Resource |
| kirby21.dti | 1.7.0 | Example DTI Data from the Multi-Modal MRI ReproducibilityResource |
| kirby21.flair | 1.7.0 | Example FLAIR Structural Data from the Multi-Modal MRIReproducibility Resource |
| kirby21.fmri | 1.7.0 | Example Functional Imaging Data from the Multi-Modal MRIReproducibility Resource |
| kirby21.mricloud | 0.0.0.9000 | A dataset containing correlation data for 20 subjects fromKennedy Krieger |
| kirby21.mt | 1.7.0 | MT Structural Data from the Multi-Modal MRI ReproducibilityResource |
| kirby21.smri | 1.5 | Example Structural Data from the Multi-Modal MRI Reproducibility Resource |
| kirby21.t1 | 1.7.0 | Example T1 Structural Data from the Multi-Modal MRIReproducibility Resource |
| kirby21.t2 | 1.7.0 | Example T2 Structural Data from the Multi-Modal MRIReproducibility Resource |
| kirby21.vaso | 1.7.0 | Example VASO Data from the Multi-Modal MRI ReproducibilityResource |
| LESYMAP | 0.0.0.9221 | Lesion to Symptom Mapping in R |
| LINDA | 0.5.1 | Lesion Identification with Neighborhood Data Analysis |
| lungct | 0.7.6.1 | Processing of Lung Computed Tomography (CT) Scans |
| malf.templates | 1.2.0 | Template Images for Multi-Atlas Label Fusion (MALF) |
| medals | 0.3.0 | Performs Memory Efficient Decomposition for Analysis of Localneighborhood moments for Segmentation |
| mimosa | 0.5.8 | MIMoSA: A Method for Inter-Modal Segmentation Analysis |
| mmand | 1.6.0 | Mathematical Morphology in Any Number of Dimensions |
| mni | 0.2.0 | Human MNI (Montreal Neurological Institute) Adult Templates |
| MNITemplate | 1.0.0 | MNI MRI Template |
| MriCloudR | 0.9.3 | R wrapper for MriCloud API |
| MRIcloudT1volumetrics | 0.3.1 | MRIcloud Analysis of T1 Volumetric Output |
| msmri | 0.3.1 | Open Multiple Sclerosis Magnetic Resonance Imaging Data |
| neurobase | 1.30.0 | Neuroconductor Base Package with Helper Functions for niftiObjects |
| neurocInstall | 0.12.1 | Neuroconductor Installer |
| neurocStats | 0.1.2 | Package that Retrieves Neuroconductor Stats |
| neurohcp | 0.8.1 | Human Connectome Project Interface |
| neurovault | 0.5.6 | Neurovault Database API Access |
| NiftiArray | 0.99.6.1 | HDF5 Delayed Array for Nifti Objects |
| nitrcbot | 1.2 | Download Image Files from the NeuroImaging Tools and ResourcesCollaboratory |
| nsrr | 0.1.5 | Interface to National Sleep Research Resource |
| oasis | 3.0.1 | Multiple Sclerosis Lesion Segmentation using Magnetic ResonanceImaging (MRI) |
| oro.asl | 0.1.1 | Rigorous - Aterial Spin Labelling |
| oro.dicom | 0.5.2.2 | Rigorous - DICOM Input / Output |
| oro.nifti | 0.10.2 | Rigorous - NIfTI + ANALYZE + AFNI : Input / Output |
| oro.pet | 0.2.5 | Rigorous - Positron Emission Tomography |
| pain21 | 0.1.1 | 21 Pain Studies |
| papayar | 1 | View Medical Research Images using the Papaya JavaScript Library |
| papayaWidget | 0.7.1 | Embed an Papaya Image Viewer |
| pbj | 0.1.6 | Parametric Bootstrap Joint Testing Procedures for Neuroimaging |
| penn115 | 0.1.1 | Template MRI Scan from 115 University of Pennsylvania Patients |
| qMRI | 1.2 | Methods for Quantitative Magnetic Resonance Imaging ('qMRI') |
| radtools | 1.0.7.2 | Utilities for Convenient Extraction of Medical Image Metadata |
| RAVEL | 1.2.2 | Removal of Artificial Voxel Effect by Linear Regression |
| RAVELData | 0.99.1 | Example dataset of input data for RAVEL |
| rcamino | 0.6.4 | Port of the Camino Software |
| RIA | 1.4.2 | Radiomics Image Analysis Toolbox for Medial Images |
| RNifti | 1.1.0 | Fast R and C++ Access to NIfTI Images |
| RNiftyReg | 2.6.7 | Image Registration Using the NiftyReg Library |
| robex | 1.2.6.1 | Robust Brain Extraction ('ROBEX') |
| ROpenCVLite | 0.3.410 | Install OpenCV |
| rtapas | 0.2.0 | TAPAS: A thresholding approach for probability map automatic segmentation automatic segmentation |
| Rvision | 0.3.5 | Basic Computer Vision Library |
| Rxnat | 1.0.8 | Queries and Extracts Images from Extensible Neuroimaging ArchiveToolkit Public/Private Datasets |
| smri.process | 0.8.4 | Processing of Structural Magnetic Resonance Imaging |
| spant | 1.2.1 | MR Spectroscopy Analysis Tools |
| spm12r | 2.8.1 | Wrapper Functions for SPM (Statistical Parametric Mapping)Version 12 from the Wellcome Trust Centre for Neuroimaging |
| sri24 | 0.1.2 | SRI24 MRI Atlas for Normal Adult Brain Anatomy |
| stapler | 0.7.2 | Simultaneous Truth and Performance Level Estimation |
| sublime0 | 1.3 | Automatic Lesion Incidence Estimation and Detection using Multi-Modality Longitudinal Magnetic Resonance Images |
| voxel | 1.3.5 | Mass-Univariate Voxelwise Analysis of Medical Imaging Data |
| waveslim | 1.8.0 | Basic Wavelet Routines for One-, Two-, and Three-DimensionalSignal Processing |
| WhiteStripe | 2.3.2 | White Matter Normalization for Magnetic Resonance Images usingWhiteStripe |