How to ensure reproducibility in Galaxy?

Setting Up a Consistent Galaxy Environment

• Ensure that all tools and versions used on Galaxy are the same every time. Keep track of tool versions and update history for reproducibility.

 

• Use the same Galaxy instance and avoid using different servers to run analyses, as configuration differences can affect results.

Documenting Every Step

• Keep a detailed record of every step, including parameters used and the sequence of operations. This helps in tracing and replicating the analysis workflow.

 

• Encourage the use of Galaxy’s history feature to save workflows, enabling easy re-run and sharing of analysis with collaborators.

Using Workflow Tools

• Leverage Galaxy's workflow editor to create and document a structured workflow. This ensures all steps are captured and can be reused.

 

• Export and save workflows as files, providing an easy way to archive and share reproducible processes.

Managing Data Inputs

• Use consistent and well-documented datasets. Ensure input data is version-controlled if possible to prevent discrepancies in analysis results.

 

• Utilize Galaxy’s data libraries to organize and manage datasets efficiently.

Verifying Results

• Regularly verify results against known benchmarks or previously published data to ensure reproducibility and reliability.

 

• Compare outputs across different runs and document any discrepancies for further investigation.

Collaborative Practices

• Share workflows and datasets with collaborators through Galaxy's sharing features to allow them to replicate and validate your findings.

 

• Encourage feedback and verification by peers, enhancing the reproducibility and trust in the results generated.