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
63/100 · DStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This NovaSeq 6000 amplicon dataset for SARS-CoV-2 contains 1.08 million short reads (315.7 million bases) with moderate quality (96.3% Q20, 88.8% Q30) and zero N-content. The notably lower Q30 (88.8%) relative to other NovaSeq amplicon runs suggests possible sequencing variability or rapid library cycling. Usable for consensus-level genomics, but more stringent filtering is recommended for variant calling. Assess per-amplicon depth before inclusion in large-scale analyses.
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