High-throughput single cell transcriptome analysis and CRISPR screen identify key β cell-specific disease genes
Pancreatic endocrine cells orchestrate the precise control of blood glucose levels, but the contribution of each cell type to diabetes or obesity remains elusive. Here we used a massively parallel single-cell RNA-seq technology (Drop-Seq) to analyze the transcriptome of 26,677 pancreatic islets cells from both healthy and type II diabetic (T2D) donors. We have analyzed cell type-specific gene signatures, and detected several rare α or β cell subpopulations with high sensitivity. We also develope...
Provenance — who produced it, who reused it
Linked to 5 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.
- Single-Cell Heterogeneity Analysis and CRISPR Screen Identify Ke... 2019 · 135 cites
- Delineating mouse β-cell identity during lifetime and in diabete... 2023 · 80 cites
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