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
81/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a human bulk RNA-seq library (Illumina HiSeq 2000, ~11.8M reads at 49 bp) that earns a solid B (81/100) on a fully measured QC pass, so the reading is not provisional — the four scored metrics were all directly observed rather than extrapolated. The grade is propped up by excellent base-call quality (mean Q34.3, 89% of bases ≥Q30) and zero detectable adapter contamination, meaning the underlying sequence is clean and trustworthy for alignment and quantification. The single factor dragging the score down is an 88.67% duplication rate, which scored 0/100; in RNA-seq some duplication is expected from genuinely high-expression transcripts, but a level this extreme points to limited library complexity and PCR over-amplification, which can distort expression estimates and undermines any use case sensitive to molecular counts (e.g. differential expression on lowly expressed genes). For reuse, the data are dependable for robustly expressed transcripts but should be treated cautiously where quantitative accuracy or rare-transcript detection matters, especially given the short 49 bp reads that limit splice-junction and isoform resolution.
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.