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.
🔒 Nothing you paste is logged or stored
Paste a FASTQ file and get the full seven-module report the FastQC desktop tool is known for, reimplemented from its own public documentation — same modules, same thresholds, straight from a paste. 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 is a native from-scratch implementation of FastQC's published methodology and thresholds, taken from Babraham Bioinformatics' own public documentation — so you get the same seven modules and the same pass/warn/fail verdicts without installing FastQC or a Java runtime. Where FastQC's docs don't publish an internal detail (for example its exact duplication-level bin boundaries), SeqBench documents the choice it makes on the tool page.
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?
No. Your FASTQ text is used only to compute the report and is never logged or stored. The same report is also available via the REST API and the MCP server.
Can it trim the reads, or only report on them?
Both. Alongside the report there is a trimmer: it removes adapter sequence with an ungapped sliding-suffix match against the same named Illumina adapters the adapter-content module checks for, then applies a BWA-style 3' quality trim (the algorithm Cutadapt's -q option reuses) at a Phred threshold of 20, and drops any read left shorter than 20 bases. You get the trimmed FASTQ back plus before/after read counts, mean length and mean quality, so you can see what the trim cost you. Paired-end trimming is not supported: reads are trimmed independently, so a pair whose mate is dropped is not removed with it.
More
Related tools
Drop a plate of Sanger reads against one construct and get one row per clone: which colonies to grow up, and why.
Screen an unknown plasmid against 30 curated common backbones and rank the candidates by identity and coverage.
Align several DNA or protein sequences and view a colored alignment with a consensus.