GSM4447249
GEO sampleProvenance — 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
100/100 · AStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is human bulk RNA-seq (expression profiling by high-throughput sequencing), and on the metrics actually measured it earns a clean A: base quality is excellent, with 98.9% of bases at Q30 and a mean base quality of 35, meaning the reads are highly accurate and well-suited to confident alignment and expression quantification. The grade is further reinforced by effectively zero adapter contamination and a low 1.54% duplication rate, indicating clean library prep and good library complexity rather than PCR-driven redundancy that would distort counts. The main caveat for reuse is the very short 28 bp mean read length, which is fine for gene-level expression but limits isoform resolution, splice-junction detection, and multi-mapping disambiguation. Note also that the score was driven almost entirely by per-base quality metrics; depth, mapping rate, and rRNA/intronic fractions were not part of this pass, so confirm sequencing depth and alignment statistics independently before relying on it for differential-expression or low-abundance transcript work.
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.