Cell-type specific profiling of human entorhinal cortex at the onset of Alzheimer’s disease neuropathology [scRNA-seq]
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 4 × Entorhinal CERAD_0 Braak_0 vs 4 × Entorhinal CERAD_B Braak_IIGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE287652_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1214196 and SRA study SRP558999. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 8 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8749389 Entorhinal CERAD_0 Braak_0 rep1 Entorhinal CERAD_0 Braa…
- GSM8749390 Entorhinal CERAD_0 Braak_0 rep2 Entorhinal CERAD_0 Braa…
- GSM8749391 Entorhinal CERAD_0 Braak_0 rep3 Entorhinal CERAD_0 Braa…
- GSM8749392 Entorhinal CERAD_0 Braak_0 rep4 Entorhinal CERAD_0 Braa…
- GSM8749393 Entorhinal CERAD_B Braak_0
- GSM8749394 Entorhinal CERAD_0 Braak_II
- GSM8749395 Entorhinal CERAD_B Braak_II rep2 Entorhinal CERAD_B Braa…
- GSM8749396 Entorhinal CERAD_B Braak_II rep3 Entorhinal CERAD_B Braa…
- GSM8749397 Entorhinal CERAD_B Braak_II rep4 Entorhinal CERAD_B Braa…
- GSM8749398 Entorhinal CERAD_B Braak_II rep5 Entorhinal CERAD_B Braa…
- GSE287651 Cell-type specific profiling of human entorhinal cortex at the onset of Alzheimer’s disease neuropathology [RNA-seq] 15 samples shares neuropathology, entorhinal, cell-type, alzheimer, specific, cortex, onset
- GSE308007 Spatial and single cell transcriptomics in the human Entorhinal Cortex across diverse risk of Alzheimer’s disease 31 samples shares entorhinal, alzheimer, cortex
- GSE86469 Single cell transcriptomics defines human islet cell signatures and reveals cell-type-specific expression changes in type 2 diabetes [single cell] 638 samples shares cell-type, specific
- GSE281106 Single-cell RNA-seq of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases [scRNAseq_KR_SGI] 352 samples shares cell-type, specific
- GSE280974 Single-cell RNA-seq of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases [scRNAseq_JP_RIK] 302 samples shares cell-type, specific
- GSE260603 Dissecting depression symptoms: multi-omics clustering uncovers immune-related subgroups and cell-type specific dysregulation 273 samples shares cell-type, specific
- GSE262793 Integrative transcriptome and proteome profiling of insulin-resistant kidney cell models and patient biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease 80 samples shares cell-type, specific
- GSE237718 APOE determines cell type-specific pathological landscape of Alzheimer's disease 56 samples shares alzheimer, specific
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.