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
83/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a small-RNA (miRNA-Seq) library from mouse run on an Illumina MiSeq, with short ~36 bp reads consistent with mature microRNA inserts. In QC terms it earns a solid B (83/100): base quality is excellent and trustworthy — pct_q30 of 96.6% and a mean base quality of 36.2 both score full marks, with zero adapter and N content, so the reads themselves are clean and reliable for mapping. The grade is held back almost entirely by a 97.27% duplication rate, which scored 0 and is the single dominant penalty; however, for miRNA-Seq this extreme duplication is largely expected biology rather than a library defect, because the small, highly expressed microRNA repertoire produces many genuinely identical reads, so a generic dedup-based penalty likely overstates the problem here. All contributing metrics were directly measured (evidence_strength is full), so this reading is not provisional — just be aware that for differential-expression reuse you should treat the duplication flag as assay-typical and verify complexity at the miRNA level rather than discarding the dataset on the raw duplication number alone.
The B 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.