CAPTURE

Build reproducible, FAIR computational workflows from start to finish.

Starting a computational science project means navigating countless decisions about structure, tooling, and reproducibility—and even experienced developers struggle to get it right.

CAPTURE (Custom Analysis Pipelines Tailored for Universal Reproducibility and Efficiency) is a framework and command line interface (CLI) that standardizes these decisions through strong conventions for project structure, execution, and validation, enabling teams to build scalable, reproducible, and FAIR workflows from start to finish.

Why CAPTURE?

CAPTURE helps you build computational science projects that are consistent, reproducible, and scalable—without reinventing the wheel each time.

• Standardized project structure: Organize data, code, and results using consistent, predictable conventions.

• Reproducible execution: Run analyses in controlled, versioned environments across HPC systems.

• Built-in validation and verification: Ensure outputs are correct and reproducible with automated checks.

• Seamless HPC integration: Scale workflows across HPC clusters without rewriting pipelines.

• Integrated version control workflows: Leverage Git and GitHub best practices for collaboration and traceability.

• Convention over configuration: Reduce decision fatigue by adopting opinionated defaults that promote best practices.

• FAIR-ready by design: Produce outputs that are Findable, Accessible, Interoperable, and Reusable.

Quick Start

Get up and running with CAPTURE in minutes by completing the following steps in an HPC terminal session.

1. Install CAPTURE

curl -sSL https://raw.githubusercontent.com/lasseignelab/capture/refs/heads/main/install.sh | bash
source ~/.bash_profile

2. Initialize a new project

cap new my-project
cd my-project

This creates a standardized project structure for data, code, results, and configuration.

3. Run an example workflow

cap run src/example.sh
head data/*

CAPTURE will execute the workflow using its built-in conventions for job execution, logging, and output organization.

4. Verify results

cap verify verifications/example.sh
git diff --quiet verifications/example.out && echo "Verification succeeded" || git diff

Outputs are checked for consistency and reproducibility. If there is no difference in verifications/example.out, the example results were fully reproduced.

Congratulations!! You now have a well-structured, reproducible computational project.

Documentation

Comprehensive CAPTURE documentation can be found here.

Contributing

We welcome contributions from both new and experienced developers.

Whether you're fixing a bug, improving documentation, or proposing a new feature, CAPTURE is designed to support reproducible, high-quality computational workflows—and contributions should follow the same principles. Contributions that improve reproducibility, validation, and portability are especially valuable.

Getting started

1. Fork the repository and create a new branch
2. Make your changes with clear, focused commits
3. Add or update tests and documentation as needed
4. Submit a pull request with a clear description of your changes

Development guidelines

• Follow CAPTURE conventions for project structure and naming
• Write reproducible, testable code
• Prefer simple, transparent solutions over complex abstractions
• Ensure scripts and workflows run consistently across environments (local, HPC, cloud)

Reporting issues

If you encounter a bug or have a feature request, please open an issue and include:

• A clear description of the problem
• Steps to reproduce (if applicable)
• Relevant logs or error messages
• Your environment (OS, HPC, container, etc.)

Code of conduct

Be respectful and constructive. We aim to foster an inclusive and collaborative community.

Tests

All pull requests must include BATS tests covering the changes.

The testing framework is installed by the following command.

tests/install

The entire test suite is executed by the following command.

tests/run

The tests can be filtered with the --filter option. This saves time by allowing subsets of the test suite to be ran while coding. The following examples of using --filter are based on this hypothetical BATS test.

@test "cap md5: All files in a folder" {
  ...
}

Examples of using --filter

How to run just the cap md5 tests:

tests/run --filter "cap md5"

How to run just the single hypothetical test:

tests/run --filter "cap md5: All files in a folder"

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Contributors

Thanks to everyone who has contributed to CAPTURE:

• Tonie Crumley
• TC Howton
• Lasseigne Lab contributors