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
67/100 · DStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This HiSeq 4000 RNA-seq from Tribolium castaneum generated 9.2M reads with perfect Q20 and Q30 (100%) across 421M bases, delivering pristine data quality ideal for detecting rare transcripts and splice variants. The 46.9% GC is expected. Reuse for high-confidence developmental transcriptomics is well-supported; caveat that moderate overall depth limits power for detecting subtle differences in lowly-expressed genes.
The D 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