CLAP is a unified platform designed to simplify the use of commonly employed neuroimaging tools, streamline research pipelines, and integrate custom-built utilities into a single, cohesive application.
- Compute New Registration: Batch processing of image registrations into a selected target space using ANTs SyN.
- Apply Existing Transforms: Batch application of precomputed spatial transforms.
- Generate Connectomes: Generate connectivity matrices from tractograms using a specified parcellation.
- Z-Score Connectomes: Visualize deviations of a connectome relative to a control cohort.
- Visualize Connectomes: Display and compare selected connectomes.
- Generate Custom sEEG Parcellation: Create parcellation images using sEEG electrode coordinates and a corresponding reference image.
- Launch Freeview: Visualize MRI data with optional preloaded overlays.
- Run recon-all: Execute the full FreeSurfer cortical reconstruction pipeline with automatic multi-core optimization.
- Run FastSurfer: Perform fast deep learning–based segmentation with optional GPU acceleration.
- Import Scripts: Centralize Python, Bash, R, MATLAB, and other scripts.
- Organize by Project: Categorize scripts with metadata including description, dependencies, and author.
- Quick Discovery: Filter and search scripts by project, language, author, or keywords.
- One-Click Execution: Run scripts directly in a terminal or open them in VS Code for editing.
- Code Preview: Inspect script contents prior to execution.
To get started with CLAP:
- Navigate to your chosen installation directory
(cd your/installation/folder) - Clone the repository
(git clone https://github.com/Squiyk/CLAP) - Navigate into the project directory
(cd CLAP) - Make the setup script executable (macOS/Linux)
(chmod +x START_CLAP_MAC_LINUX.sh) - Launch the application to initialize its environment
(./START_CLAP_MAC_LINUX.sh) - To update CLAP after new commits, navigate to the
CLAPdirectory and run
(git pull)
Alternatively, you may download the repository as a ZIP archive from GitHub, extract it, and follow steps 4 and 5.
Within the application’s settings, you can view which external dependencies were detected on your system’s PATH and manually specify custom paths for any that were not automatically found.
CLAP relies on the following external tools:
- ANTs (Advanced Normalization Tools) — required for image registration
- MRtrix3 — required for tractography and connectome generation
- FreeSurfer — required for cortical reconstruction and visualization (license required)
- FastSurfer — optional alternative for accelerated deep learning–based segmentation