Reproducible Multi-Omics Analysis Pipelines

Reproducibility is the foundation of trustworthy bioinformatics. In this note I share the pipeline conventions we now enforce in our lab.

Containerize everything

# docker-compose service snippet
services:
  pipeline:
    image: ghcr.io/our-lab/omics-pipeline:2026.09
    volumes:
      - ./data:/data
      - ./results:/results

Every analysis runs inside a versioned container. Pin versions, not just package names.

Track data provenance

For each result file we record:

1. Input data version (checksum or DOI)
2. Pipeline commit hash
3. Software versions (conda list --export)
4. Random seed for every stochastic step

A minimal project layout

project/
├── data/raw/       # never modified
├── data/processed/
├── src/            # pipeline code
├── results/
└── report/

If a collaborator cannot reproduce your figure from this layout in one command, the pipeline is not done yet.