Welcome to the Fairflow-BioinformaticsFramework organization. We provide a suite of tools and a framework designed to make bioinformatics analyses verifiable, reproducible, and transparent by construction.

Our Mission: To turn bioinformatics scripts into auditable, ready-to-run pipelines by combining immutable containerization with a declarative interface specification.

Computational reproducibility is often compromised by hidden dependencies and environment drift. FairFlow addresses this by decoupling the pipeline logic from the execution environment.

Our approach relies on two pillars:

1. Immutable Containers: Environments built with CREDO that are fully pinned and time-stable.
2. Declarative Interfaces: Defined in Baryon (Baryon Language), specifying generic inputs/outputs that can be transpiled into any frontend (R, Python, Bash, Galaxy, Nextflow, Streamflow).

This ensures that your analysis yields identical outputs across different operating systems (Linux, macOS, Windows) and hardware architectures.

Here is an overview of the repositories in this organization and their roles in the framework.

• Tutorial_Fairflow: Start Here! The canonical guide to the FairFlow path. It covers everything from building containers to writing .bala files.
• Tutorial_CARNGS: Specific tutorials for the CAR-NGS suite of pipelines.

• Baryonlang: The Baryon compiler (Python). Reads .bala specification files and generates ready-to-run scripts for R, Python, Bash, Galaxy, Nextflow, and Streamflow.
• DockerBuilder: Helper scripts and templates for building reproducible Docker images using CREDO. Safeguards against "dependency drift".

FairFlow makes it easy to bring your tools into Galaxy without complex configuration.

• galaxy-formed: An immutable, Dockerized Galaxy distribution pre-configured to work with Baryon.
• lemaitre: A lightweight service for drag-and-drop tool installation into Galaxy. Upload your generated wrapper, and it appears in Galaxy instantly.
• galaxy-formation: Ansible playbooks for setting up the Galaxy environment.
• docker-galaxy: Infrastructure for the Galaxy container.

CAR-NGS is our flagship suite of NGS pipelines (16S, RNA-seq, ATAC-seq, etc.) built entirely with FairFlow.

• CAR-NGS: The Frontend. Contains the auto-generated R functions that users install to run analyses.
• CAR-NGS_Backend: The Backend. Contains the Docker build contexts (scripts, Dockerfiles) for the pipelines.

1. Read the Paper: FairFlow: A Transparency-First Framework for Verifiable and Reproducible Bioinformatics.
2. Follow the Tutorial: Go to Tutorial_Fairflow to build your first reproducible pipeline.
3. Use an Existing Pipeline: Install CAR-NGS in R to run verified NGS workflows.

# Example: Installing CAR-NGS
library(devtools)
install_github("https://github.com/Fairflow-BioinformaticsFramework/CAR-NGS", ref="main")

Maintained by the FairFlow Team.