📊 Genomics QC

Quality control for genomic sequencing data. Wraps FastQC, MultiQC, and fastp for read-level QC and adapter trimming.

CLI Reference

python omicsclaw.py run genomics-qc --demo
python omicsclaw.py run genomics-qc --input <reads.fastq> --output <dir>

Why This Exists

• Without it: Traces of adapters, low-quality reads or overrepresented sequences break downstream assemblies/alignments
• With it: Reads are automatically trimmed, masked, and summarized
• Why OmicsClaw: Simplifies execution of widely used tools like FastQC and fastp simultaneously

Workflow

1. Calculate: Map out local file metadata and basic stats.
2. Execute: Calculate quality heuristic per base pair position.
3. Assess: Detect adapters and k-mer enrichment.
4. Generate: Output trimmed sequences and MultiQC reports.
5. Report: Tabulate key pass/fail thresholds.

Example Queries

• "Run FastQC on these fastq files"
• "Trim adapters using fastp"

Output Structure

output_directory/
├── report.md
├── result.json
├── processed.fastq.gz
├── figures/
│   └── gc_content.png
├── tables/
│   └── basic_statistics.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    └── checksums.sha256

Safety

• Local-first: Strict offline processing without external upload.
• Disclaimer: Requires OmicsClaw reporting structures and disclaimers.
• Audit trail: Hyperparameters and operational flow states are logged fully.

Integration with Orchestrator

Trigger conditions:

• Automatically invoked dynamically based on tool metadata and user intent matching.

Chaining partners:

• <raw_data_ingest>

  — Upstream sample integration

• align

  — Downstream read alignment

Citations

• FastQC
• fastp