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 NovaSeq 6000 amplicon run for SARS-CoV-2 yielded 476,451 short reads (139.1 million bases) with good quality (98.3% Q20, 95.1% Q30). The 41.2% GC content is slightly elevated compared to most SARS-CoV-2 amplicon runs, potentially reflecting sample-specific viral diversity. Moderate read count suits targeted studies of a small amplicon set. Clean quality metrics enable reliable variant and consensus calling.
The D grade is a transparent weighted average. Each metric below scored from 0–100% against the published amplicon 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