PRJNA279780
BioProjectProvenance — 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
95/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is high-throughput bulk RNA-seq from the Asian longhorned beetle (Anoplophora glabripennis) on an Illumina HiSeq 2000, and it earns a well-supported A (95/100): every metric that actually drove the score was directly measured (evidence_strength = 1), so this is a firm reading rather than a provisional one pending deeper analysis. The grade is anchored by excellent base accuracy — 96.2% of bases at Q30 and a mean base quality of 37 — meaning the underlying reads are trustworthy for sensitive applications like variant calling and accurate transcript quantification. The one real drag is a 43.12% duplication rate (scored 71/100), which is common in RNA-seq from highly expressed transcripts and PCR amplification but does inflate apparent read depth, so you should deduplicate or account for library complexity before treating coverage as effective depth. With low adapter (2.11%) and negligible N content, the dataset is clean and reusable; just enter it expecting that a meaningful fraction of reads are redundant.
The A 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
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.