FASTQ Reads — Phred+64 Legacy Encoding (.fastq)
The identical reads and identical quality scores written with the legacy Phred+64 offset used by older Illumina pipelines. Decode it with the modern offset and every base looks 31 points better than it is, which is a silent quality inflation rather than a parse failure.
@NX_READ_001 length=60
GGCGCGCACGTGGGGGCCCCCAAAAAGCTCTAATGGACTGAATATTGGGGCGTTCTGATA
+
efgegdfdecfcefgcgdddbbefbeeacbeadecacbd```bbdaa_b`a_`b`b__aa
@NX_READ_002 length=60
AACTATCTTAGATAAGAGTAGACGAGAGCAACCAGACTACTTGTTGTGGGCTGCGAGGAC
+
fgeggdfeecegcddffeeedccceceededcaecbdcddcb`bc`c`aaaaca`^_bb_
@NX_READ_003 length=60
AGCGACAGATATAGCTTACCGCCGCGGCTATAAGCAAAGTGTGTCAACGAACGGCTTTCT
+
heeehgdhfgdcffgcfgdccfeffbeabacbcdccabbbdddadababc`aacb``aab
@NX_READ_004 length=60
CAAGAGCATGGGCCCAATCCGTTGATTACTGAGCTTCATCGGATCCATTAACCGTCGGGT
+
gdedddhgheefgdfcdgbebfffdfcceddebbdad`cacbbdb_abaacc`c^^`a^^
@NX_READ_005 length=60
ACGGCAAGCCGAAAAGATATTATTGATTGATCTTACATTCGATCGGTTCGCAGACCCGAG
+
heghefdggdfdfefefefcdffbcbeebcdeedddcbabcbd`c``ba__bcaab__bb
@NX_READ_006 length=60
ACCCGCAGTTTGGAGTGCCTAGCGACTAATGTGACACTGTGGTATCGCTCCTTCTTAGGA
+
ffhehgdhddgdefegfebbefdefcfdbbdbcaaab`ccca`aac``_cc`a`ba_`_`
Specifications
- Reads
- 6
- Read Length
- 60
- Encoding
- Phred+64
- Ascii Offset
- 64
- Identical Scores To
- the Phred+33 twin
- Trap
- decoding with offset 33 inflates every score by 31
Testing contract
Expected to pass- Scenario
- Decode the quality strings with offset 64 and compare the resulting scores against the Phred+33 twin.
- Expected result
- The two files yield identical score arrays when each is decoded with its own offset; decoding this file with offset 33 inflates every score by exactly 31.
What is a .fastq file?
FASTQ pairs each sequence with per-base quality scores. A record is exactly four lines: a `@` header, the sequence, a `+` separator that may repeat the header, and a quality line of the same length whose characters encode Phred scores as ASCII with an offset — 33 in the Sanger/Illumina 1.8+ encoding, 64 in older Illumina data. Misidentifying that offset silently shifts every quality value by 31.
How to use this file
Use an example .fastq file to test read parsers, quality-trimming tools, and encoding detection, verifying that sequence and quality lengths match, that a `@` at the start of a quality line is not mistaken for a new record, and that the documented offset is applied.
How to use this file for testing
“FASTQ Reads — Phred+64 Legacy Encoding (.fastq)” is a deterministic Novus Examples fixture for Scientific data, Editor testing, Conversion testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: Phred+64. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
Related files
- fastaFASTA Contigs — One Line Per Record (.fasta)The same four contigs written one sequence per line rather than wrapped, which is how many pipelines emit FASTA and how many line-oriented parsers assume it always looks. Comparing against the wrapped twin proves a parser joins continuation lines instead of taking the first one.
- csvGenomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)Every interval written in both coordinate conventions with its length, which is identical either way. It is the lookup table for the most common bioinformatics off-by-one, and the length column is what proves a conversion did not quietly change an interval's size.
- nwkNewick Tree — Topology Only, No Branch Lengths (.nwk)The identical tree topology with every branch length and support value stripped, which is what a Newick writer produces when the source tree has no lengths. Comparing the two proves a parser distinguishes 'length zero' from 'no length recorded'.
- csvSAM CIGAR Span Reference — Query versus Reference Length (.csv)Each alignment's CIGAR decomposed into how many query bases and how many reference bases it consumes, with the resulting 1-based reference end. The three records where those numbers differ are the whole reason CIGAR arithmetic is worth testing.
- csvChemistry Fixture Molecule Index (.csv)One row per molecule used across the chemistry fixtures, with formula, molecular weight, SMILES and the atom and bond counts each file should yield. It is the oracle a cheminformatics toolkit can be scored against without needing a second toolkit to generate the answers.
- csvDICOM-Shaped Dataset — Element Table Reference (.csv)Every element of the synthetic phantom dataset as tag, value representation, meaning and encoded length, in the ascending tag order the standard mandates. Diff a parser's element list against it to check both the ordering rule and the two different length encodings.
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