FASTQ quality assessment for bulk RNA-seq — Phred scores, GC content, adapter detection, read length distribution, Q20/Q30 rates.
Quality assessment of raw FASTQ files for bulk RNA-seq experiments. Computes per-base quality scores, GC content, adapter contamination, read length distribution, and Q20/Q30 rates — a Python implementation of core FastQC metrics.
| Format | Extension | Description |
|---|---|---|
| FASTQ | .fastq, .fq, .fastq.gz | Raw sequencing reads |
python omicsclaw.py run bulkrna-read-qc --demo
python omicsclaw.py run bulkrna-read-qc --input reads.fastq.gz --output results/
output_directory/
├── report.md
├── result.json
├── figures/
│ ├── per_base_quality.png
│ ├── gc_content.png
│ ├── read_length_distribution.png
│ └── quality_score_distribution.png
├── tables/
│ └── qc_summary.csv
└── reproducibility/
└── commands.sh
bulkrna-read-alignment — Downstream: alignment after QCbulkrna-qc — Downstream: count matrix QC after quantification