Sequencing metadata QA before workflow execution

MetaSheet-Guard

Experimental-design-aware quality control, auditable repair, and workflow export for sequencing analysis sample sheets.

Start with the quickstart Explore validator rules

MetaSheet-Guard checks sequencing analysis metadata at the analysis-preparation stage: after FASTQ generation or public metadata collection, but before running downstream workflows such as Nextflow, Snakemake, nf-core/rnaseq, or custom RNA-seq pipelines.

Model the experiment

Build a canonical representation of biological samples, sequencing runs, lanes, FASTQ files, technical replicates, biological replicates, conditions, batches, and design variables.

Catch workflow blockers

Detect missing required columns, duplicate headers, empty required values, FASTQ path problems, paired-end mismatches, metadata conflicts, and export readiness issues.

Audit safe repairs

Apply conservative metadata repairs, such as alias normalization and whitespace cleanup, while writing a reproducible changes.json provenance record.

Export cleaned sheets

Produce canonical CSV output, nf-core/rnaseq-compatible sample sheets, Snakemake inputs, and DESeq2 design tables from checked metadata.

Where It Fits

1

Start with CSV, TSV, nf-core/rnaseq-style, or SRA-like metadata.

2

Validate table structure, FASTQ files, sample/run links, and design risks.

3

Repair only safe metadata issues and keep a machine-readable audit trail.

4

Export a clean sample sheet for downstream workflow execution.

Quickstart command

Check a dirty bulk RNA-seq sample sheet

metasheet-guard check examples/broken/missing_required_column.csv \
  --schema bulk-rnaseq \
  --json report.json

Example Issue Codes

• REQUIRED_COLUMN_MISSING
• FASTQ_PAIR_NAME_MISMATCH
• SAMPLE_METADATA_CONFLICT
• BATCH_CONDITION_CONFOUNDED

Explicit Non-goals

MetaSheet-Guard is not an aligner, quantifier, differential-expression engine, SRA downloader, Illumina SampleSheet validator, or replacement for workflow-specific schema validators.