Transcriptomic and proteomic landscape of mitochondrial dysfunction reveals secondary coenzyme Q deficiency in mammals
Differential gene expression in mouse models of mitochondrial dysfunction
Provenance — who produced it, who reused it
Linked to 3 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.
- Transcriptomic and proteomic landscape of mitochondrial dysfunct... 2017 · 281 cites
- mitoXplorer, a visual data mining platform to systematically ana... 2019 · 87 cites
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
85/100 · BStandardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured
This is a bulk RNA-seq dataset from mouse, and on balance it is a solid, reusable resource that earned its B (85/100) on the strength of genuinely measured, high-quality base calls. The grade is driven up by excellent sequencing accuracy — 98.1% of bases at Q30 and a mean base quality of ~39.9, with zero detectable adapter contamination — meaning reads are clean and base-level errors are unlikely to confound expression estimates. The single factor pulling the score down is a duplication rate of 70.19% (scored just 11/100), which is high but not unusual for RNA-seq of highly expressed transcripts; for reuse it matters because it inflates apparent read depth and can bias quantification, so deduplication and library-complexity checks are advisable before differential-expression work. Because every contributing metric here was actually measured (evidence_strength=1), this reading is not provisional — the only gap is an upstream HTTP 429 fetch error on ancillary metadata, which does not affect the QC values reported.
The B 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.