FASTQ Deep QC Report — FastQC-Style Read Quality Control
Per-base quality, GC and length distributions, duplication levels, overrepresented sequences and adapter content, each with a warn/fail verdict.
🌐 Runs on the SeqBench API — also callable via REST & MCP, and in bulk from the batch tools
Paste a FASTQ file and get the full seven-module report the FastQC desktop tool is known for, reimplemented from its own public documentation as a stateless, server-side check — no install, no Java, no waiting on a shared cluster. Per-base sequence quality is drawn as a box-and-whisker plot across read positions; per-base content overlays %A/%C/%G/%T; per-sequence GC content is compared against a theoretical normal distribution fit to your data's own modal GC%; duplication levels and overrepresented sequences use FastQC's own documented 100,000-read sampling scheme; and adapter content screens for the real Illumina TruSeq, Nextera and small-RNA adapter sequences. Every module gets an explicit pass/warn/fail verdict against FastQC's own published thresholds, not just a chart to eyeball.
Paste a FASTQ file (or load the example) to run the deep QC report.
How to use the FASTQ QC Report tool
- 1Paste FASTQ text (four lines per read: '@id', sequence, '+', quality) or load the example, and pick the Phred quality encoding.
- 2Review each module's chart and its pass/warn/fail badge — per-base quality/content, GC and length distributions, duplication levels, overrepresented sequences, and adapter content.
- 3Export any chart as SVG/PNG for your notebook, or share a link that reproduces the exact report.
Frequently asked questions
Is this the same as running FastQC?
It reimplements FastQC's published methodology and thresholds (from Babraham Bioinformatics' own public documentation) as a native, from-scratch server-side calculation — not a wrapper around the FastQC Java tool itself, which is GPL-licensed. Verdicts and chart conventions closely track FastQC's public docs, but exact internal implementation details FastQC's docs don't publish (e.g. its precise duplication-level bin boundaries) are SeqBench's own reasonable choices, noted in the tool's own documentation.
Which adapters does the adapter content module check for?
The real Illumina TruSeq (and the shared Illumina Universal 13bp prefix), Nextera transposase, and small RNA 3' (RA3) adapter sequences, sourced from Illumina's own current public adapter-sequence documentation. A read is counted as containing an adapter from its first occurrence position through to the end of the read, matching FastQC's own documented semantics.
How are sequence duplication levels and overrepresented sequences sampled?
Following FastQC's own documented approach: new distinct sequences are only tracked from the first 100,000 reads (bounding memory on very large files), but every subsequent read still increments the count for a sequence already being tracked. The dedup/overrepresentation key is a read's first 50bp once it's longer than 75bp, and the full read otherwise.
Is my data stored?
Your FASTQ text is sent to the SeqBench API to compute the report and is not stored. The stateless report is also available via the REST API and the MCP server.