Runtime Output Validation

runtime-output-validation

License: restricted — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution.

Summary

Validation of Nextflow workflow runtime outputs to confirm correct execution and data integrity of metabolomics pipeline runs. This skill ensures that workflow invocations complete successfully and produce expected results by capturing and examining runtime artifacts.

When to use

After invoking a Nextflow workflow via make run or equivalent command, to confirm the workflow executed without errors and generated expected output files. Use this skill as a post-execution check when deploying the Reverse_metabolomics_library_generation template or any Nextflow-based metabolomics pipeline.

When NOT to use

• When the workflow has not yet been executed — validation only makes sense post-execution
• When using only dry-run or preview modes; validation requires actual data generation and file output
• When external dependencies (conda, mamba, nextflow binary) are missing; resolve installation first before validating outputs

Inputs

• Nextflow workflow execution logs (stdout/stderr)
• Generated output artifacts from workflow run
• Expected output schema or baseline comparison file

Outputs

• Validation report (pass/fail assessment)
• List of generated output files with metadata
• Error log summary (if any)

How to apply

After executing make run on the Nextflow workflow, capture all standard output, error logs, and generated artifacts (output files, intermediate results, logs). Compare the captured outputs against a reference baseline or schema: verify that expected output files exist, contain non-empty data, and follow anticipated format conventions (e.g., file extensions, directory structure). Check for absence of error messages or warning flags in the execution logs. Document whether the workflow completed with exit status 0 and whether all downstream tasks finished successfully. This validation confirms both computational correctness and data pipeline integrity before downstream analysis or deployment.

Related tools

• Nextflow (Workflow execution engine that generates runtime logs and output artifacts to be validated) — https://www.nextflow.io/docs/latest/index.html
• make (Build automation tool that invokes the Nextflow workflow via the make run target; validation captures its output)

Examples

make run 2>&1 | tee run.log && grep -E '(error|Error|ERROR)' run.log || echo 'Workflow completed without errors'; ls -lh results/

Evaluation signals

• Workflow exit status is 0 (successful completion)
• All expected output files are present in designated directories and are non-empty
• No error or critical warning messages appear in execution logs
• Output file formats match expected schema (correct file extensions, content structure)
• Workflow runtime completes within reasonable time window and memory constraints

Limitations

• Validation success does not guarantee biological correctness or scientific validity of results — it only confirms technical execution
• Output validation depends on availability of conda, mamba, and nextflow installations; missing dependencies will cause workflow failure before validation stage
• Validation signals must be customized per workflow; generic file existence checks may miss domain-specific correctness criteria

Evidence

• [readme] To run the workflow to test simply do make run: "To run the workflow to test simply do"
• [other] Capture and validate the runtime outputs generated by the workflow execution: "Capture and validate the runtime outputs generated by the workflow execution"
• [readme] You will need to have conda, mamba, and nextflow installed to run things locally.: "You will need to have conda, mamba, and nextflow installed to run things locally."