Corpus 1,272 assessed · 1,173 scored · 643 reproduced ≥75 · 168 flagged ·∅ 74.1/100
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GSE107947

GEO first seen 2018

Dissection of influenza infection in vivo by single-cell RNA-sequencing

Organism
Mus musculus
Samples
10
Type
Expression profiling by high...
Submitted
2017-12-11

The influenza virus is a major cause of morbidity and mortality worldwide, yet, the impact of intracellular viral invasion and the cellular response diversity remain uncharacterized. By massively parallel single-cell RNA-seq we comprehensively mapped the host lung response to in-vivo influenza infection in wild-type and Irf7-knockout mice across nine immune and non-immune cell types. We found an unexpected high prevalence of infected cells in all cell types, showed that infection is a characteri...

Provenance — who produced it, who reused it

Linked to 2 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.

Deposited / produced by
Irit Gat-ViksIdo AmitYael SteuermanMerav CohenLiran ValadarskyEyal DavidAmit Frishberg
Reused by

1 further paper cites this accession but reuse could not be confirmed.

Deep data QC

79/100 · C

Standardized, field-standard QC computed by touching the data — every metric states how it was obtained · evidence: measured

What this means
claude:opus

This dataset is mouse bulk RNA-seq, and the C grade (79/100) reflects a fundamental tension: per-base accuracy is excellent but the quality summary is unusually flat, which tempers confidence. The two metrics steering the grade are mean_base_quality and duplication_rate: a mean Phred of 30 is mediocre-to-borderline for modern Illumina data and is the single biggest drag on the score, signaling that reads carry roughly 1-in-1000 base-call error that can blunt sensitivity for low-frequency variants or precise splice/expression calls, while a 42% duplication rate is moderately high and points to limited library complexity or PCR/optical redundancy that can inflate apparent counts. On the reassuring side, essentially 100% Q20/Q30 base fractions plus negligible adapter (0.03%) and N content indicate clean, well-trimmed reads with little technical contamination, so the data are reusable for standard differential-expression work if you account for duplication. Note, however, that the QC fetch failed (HTTP 429) and several headline numbers (100% Q30 alongside a mean quality of only 30) look internally inconsistent or capped, so this reading should be treated as provisional pending a full measured re-run.

Data type / assay
bulk-RNA-seq
Organism
Mus musculus
Metrics (value · how obtained)
n content pct 0.012 measured
pct q20 bases 100 measured
pct q30 bases 100 measured
gc content pct 49.2 measured
mean read length 66 measured
mean base quality 30 measured
adapter content pct 0.03 measured
duplication rate pct 42.37 measured
How this grade was computed
Weighted mean of 4 scored metric(s) → 79/100

The C 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.

pct q30 bases 100 measured ×1 100%
mean base quality 30 measured ×0.6 33%
adapter content pct 0.03 measured ×0.4 100%
duplication rate pct 42.37 measured ×0.4 73%
QC cost 19 s compute

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.

1 studies use it mean score 68