Provenance — who produced it, who reused it
Linked to 3 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.
3 further papers cite 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
SRR1979118 is a bulk RNA-seq library from tea plant (Camellia sinensis) sequenced on the Illumina HiSeq 2000, and on the metrics actually measured it earns a clean A: this is high-quality, reusable data. The grade is driven up by excellent base quality (Q30 = 92.3%, mean Phred 36.2) and a complete absence of adapter contamination (0%), meaning reads can be trusted largely as-is for alignment and expression quantification with minimal trimming, while the moderate 20.8% duplication rate is entirely normal for RNA-seq — it reflects expression of highly transcribed genes rather than a library-complexity problem — and so did not penalize the score. One caveat for transparency: the evidence_strength is 1, but the foundational counts (total_reads ~133M, total_bases) are reported from the archive rather than independently measured, so the headline throughput should be treated as provisional until a measured pass confirms it; the per-base quality metrics that most matter for variant or expression work, however, were genuinely measured and are solid. In short, the sequence quality is strong enough to reuse with confidence, with the only soft spot being that read/base totals rest on reported rather than verified figures.
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.