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
38/100 · FStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
RNA-Seq of Apis mellifera on an Illumina HiSeq 2500 generates ~20 million reads at moderate base quality (89.5% ≥Q20, 58.8% ≥Q30), indicating potential quality issues or sequencing artifacts in this honey bee transcriptome dataset despite substantial read count and bases. The lower Q30 percentage suggests careful quality filtering is essential. Reuse requires thorough quality assessment and downstream validation.
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