SRX326766
SRAProvenance — who produced it, who reused it
Linked to 0 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.
No linked papers found in the corpus yet.
Deep data QC
80/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a deep whole-genome shotgun (WGS) Illumina HiSeq 2000 dataset for the Asian longhorned beetle (Anoplophora glabripennis), comprising ~206M 101-bp reads (~41.7 Gb), and it earns a solid grade B (80/100): broadly reusable but not pristine. The grade is held back chiefly by pct_q30_bases at 83.1% — meaning roughly one in six bases falls below Q30, which modestly erodes confidence at read ends and will translate into more base-calling noise during variant calling or assembly, though the Q20 rate of 91.9% and mean base quality of Q33.4 indicate the bulk of the data is reliable. On the positive side, near-zero adapter content (0.97%) and a moderate, manageable duplication rate (10.6%) mean little library or trimming cleanup is needed before use, and low N-content and a stable GC of 37.1% suggest no gross contamination or compositional artifacts. Note that the evidence_strength flag is low because the headline yield figures (total reads and bases, checksum) are reported rather than independently measured, so treat the depth/throughput claims as provisional pending a full measured pass, even though the core per-base quality metrics here were directly measured and can be trusted.
The B grade is a transparent weighted average. Each metric below scored from 0–100% against the published WGS 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.