Mapping the Single Cell Transcriptomic Response of Murine Diabetic Kidney Disease to Therapies
In this study, we utilized the db/db, uninephrectomy and renin-hypertension mouse model. We compared vehicle to ACE inhibitor, Rosiglitizone, SGLT2 inhibitor, ACEi + Rosiglitizone and ACEi + SGLT2i at two time points (2 days and 2 weeks). We generated snRNA-seq datasets from all groups comprising nearly 1 million cells. Analysis of the resulting atlas revealed that the different medications affected strikingly different cell types. Combination therapy had the largest effects, but these effects w...
Provenance — who produced it, who reused it
Linked to 4 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.
3 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
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently