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
26/100 · FStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a human microRNA sequencing run (miRNA-Seq on Illumina HiSeq 2000), and in QC terms it fails outright (26/100, grade F), meaning it is not recommended for reuse without serious caveats. The grade was driven down most by an extreme duplication rate of ~79% — though for small-RNA libraries some of this is expected, since the miRNA pool is low-complexity and short reads collapse onto identical sequences, so this metric should be interpreted cautiously rather than taken as pure library failure — and by weak base quality, with only 72.3% of bases at Q30 and a mean Phred of 29.2, which erodes confidence in precise read alignment and miRNA isoform/variant calling. The one clear positive is essentially negligible adapter contamination (0.11%), notable because the short ~25.7 bp reads sit right at the adapter-readthrough danger zone, so clean adapter trimming here is genuinely reassuring. Note that evidence_strength is the lowest possible (1): core volume figures (total reads/bases, checksum) are only reported rather than independently measured, so while the quality metrics themselves were measured, the overall picture remains provisional pending a deeper verified pass.
The F 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.