A single-cell atlas of the human cortex reveals drivers of transcriptional changes in Alzheimer’s disease in specific cell subpopulations
There is currently little information about how individual cell types contribute to Alzheimer’s disease (AD). Here, we applied single-nucleus RNA-seq (snRNA-seq) on the entorhinal cortex from control and AD brains of twelve individuals, yielding a total of 13,214 high quality nuclei. We detail cell-type-specific gene expression patterns, unveiling how transcriptional changes in specific cell subpopulations contribute to AD. We report that the AD risk gene, APOE, is specifically repressed in AD o...
Provenance — who produced it, who reused it
Linked to 20 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.
- scGNN is a novel graph neural network framework for single-cell... 2021 · 457 cites
- DSTG: deconvoluting spatial transcriptomics data through graph-b... 2020 · 231 cites
- Interpretable deep learning translation of GWAS and multi-omics... 2022 · 103 cites
- Graph embedding and Gaussian mixture variational autoencoder net... 2023 · 95 cites
- Polygenic regression uncovers trait-relevant cellular contexts t... 2023 · 94 cites
15 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
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.