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
80/100 · 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 on the HiSeq 2000, and as a reuse candidate it is solidly trustworthy at grade B: base quality is excellent (88.8% of bases ≥Q30, mean base quality 33.9) and adapter contamination is effectively zero, the two metrics that most lifted the score and that matter most for accurate miRNA mapping and quantification. The grade was held back almost entirely by an 82.88% duplication rate, which scored 0 in the rubric — but for miRNA-Seq this is largely expected biology rather than a defect, since the transcriptome is dominated by a few short, highly abundant species and a 50 bp read length, so optical/PCR duplicates and genuine repeated reads are hard to distinguish and high duplication is normal here. All four scoring metrics are directly measured (evidence_strength = 1), so this reading is not provisional; the practical caveat is interpretive, namely that you should not treat the duplication penalty as a true quality failure for a small-RNA assay. In short, the reads are clean and reliable for miRNA expression analysis, with the duplication flag best read as an artifact of applying a generic RNA-seq rubric to a small-RNA library.
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.