Provenance — who produced it, who reused it
Linked to 1 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a deep-sequenced bulk RNA-seq run from the firefly Lucidota atra on Illumina HiSeq 2000, and it earns a clean A (100/100) that is fully trustworthy because every metric driving the score was directly measured rather than reported or extrapolated (evidence_strength=1), so this is a definitive QC reading, not a provisional one pending a deeper pass. The grade is anchored by the highest-weighted metric, pct_q30_bases at 94.9%, paired with a mean base quality of 36.8 — both indicate that the overwhelming majority of base calls are highly accurate, which is exactly what you want for confident expression quantification and variant or splice-junction calling on reuse. Adapter contamination is negligible (0.5%) and the 16.77% duplication rate is well within the normal range for RNA-seq, where high-expression transcripts naturally generate duplicate reads, so it reflects biology rather than a library-prep defect. The only minor caveat is that read depth, base totals, and checksum integrity are vendor-reported rather than independently re-measured, but none of these affect the per-base quality verdict, and at ~364M 100 bp reads the dataset is more than deep enough to reuse with confidence.
The A grade is a transparent weighted average. Each metric below scored from 0–100% against the published bulk-RNA-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.