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Single-cell RNA-seq reveals the transcriptional landscape and heterogeneity of aortic macrophages in murine atherosclerosis
We have applied single-cell RNA sequencing as an unbiased profiling strategy to interrogate and classify aortic macrophage heterogeneity at the single-cell level in atherosclerosis.
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.
Deposited / produced by
Clément CochainEhsan VafadarnejadPanagiota ArampatziJaroslav PelisekHolger WinkelsKlaus LeyDennis WolfAntoine E SalibaAlma Zernecke
Reused by
- Lipid-associated macrophages transition to an inflammatory state... 2023 · 119 cites
2 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
Data type / assay
bulk-RNA-seq
Organism
Mus musculus
Instrument
Illumina HiSeq 2500
Platform
ILLUMINA
Read type
short-read
Files available
FASTQ (raw reads), BAM/CRAM (aligned)
N numbers (samples, groups)
5 / 5 runs
Completeness
100%
Metrics (value · how obtained)
checksum ok
yes
reported
total bases
41741295448
reported
total reads
449979076
reported
supplementary file types
CSV, H5, TAR, TXT
reported
QC cost
10 s compute
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently