Signaling basis of gastric epithelial cell differentiation revealed by human and mouse organoids [RNA-Seq]
Single-cell RNA-seq · mouse · 32 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 32 samples: 16 conditions, mostly in duplicateGroups 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.
- Paper
- The critical role of BMP signaling in gastric epithelial cell differentiation revealed by organoidsCell regeneration (London, England) · 2025
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 GSE269973_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 PRJNA1124536 and SRA study SRP514213. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 32 samples.
How we read this: 16 replicated groups read from 32 sample titles; they account for 32 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.
- GSM8331656 AK3 2W CP CON-1 AK3 2W CP CON
- GSM8331657 AK3 2W CP CON-2 AK3 2W CP CON
- GSM8331658 AK3 2W CP KO-1 AK3 2W CP KO
- GSM8331659 AK3 2W CP KO-2 AK3 2W CP KO
- GSM8331660 AK3 2W ANT CON-1 AK3 2W ANT CON
- GSM8331661 AK3 2W ANT CON-2 AK3 2W ANT CON
- GSM8331662 AK3 2W ANT KO-1 AK3 2W ANT KO
- GSM8331663 AK3 2W ANT KO-2 AK3 2W ANT KO
- GSM8331664 AK3 4W CP CON-1 AK3 4W CP CON
- GSM8331665 AK3 4W CP CON-2 AK3 4W CP CON
- GSM8331666 AK3 4W CP KO-1 AK3 4W CP KO
- GSM8331667 AK3 4W CP KO-2 AK3 4W CP KO
- GSM8331668 AK3 4W ANT CON-1 AK3 4W ANT CON
- GSM8331669 AK3 4W ANT CON-2 AK3 4W ANT CON
- GSM8331670 AK3 4W ANT KO-1 AK3 4W ANT KO
- GSM8331671 AK3 4W ANT KO-2 AK3 4W ANT KO
- GSM8331672 S4 2W CP CON-1 S4 2W CP CON
- GSM8331673 S4 2W CP CON-2 S4 2W CP CON
- GSM8331674 S4 2W CP KO-1 S4 2W CP KO
- GSM8331675 S4 2W CP KO-2 S4 2W CP KO
- GSM8331676 S4 2W ANT CON-1 S4 2W ANT CON
- GSM8331677 S4 2W ANT CON-2 S4 2W ANT CON
- GSM8331678 S4 2W ANT KO-1 S4 2W ANT KO
- GSM8331679 S4 2W ANT KO-2 S4 2W ANT KO
- GSM8331680 S4 4W CP CON-1 S4 4W CP CON
- GSM8331681 S4 4W CP CON-2 S4 4W CP CON
- GSM8331682 S4 4W CP KO-1 S4 4W CP KO
- GSM8331683 S4 4W CP KO-2 S4 4W CP KO
- GSM8331684 S4 4W ANT CON-1 S4 4W ANT CON
- GSM8331685 S4 4W ANT CON-2 S4 4W ANT CON
- GSM8331686 S4 4W ANT KO-1 S4 4W ANT KO
- GSM8331687 S4 4W ANT KO-2 S4 4W ANT KO
- GSE307773 Oncogenic MAPK signalling induces epithelial cell state change and therapeutic resistance in vivo [RNA-Seq] 175 samples shares epithelial, rna-seq
- GSE205410 Multiple subpopulations in medullary thymic epithelial cells are regulated by Aire with distinctive modes of gene regulations [bulkRNA-seq] 47 samples shares epithelial, rna-seq
- GSE248585 A conserved epithelial wound-like transcriptional program driven by FOSL1 underlies malignant progression of pancreatic ductal adenocarcinoma (ssRNA-Seq) 46 samples shares epithelial, rna-seq
- GSE263080 RNA-sea of Smad4 wild-type or Smad4 knockout KPC PDAC organoids from monocultures or co-cultures with pancreatic stellate cells and RNA-seq of flow-sorted PSCs from the same co-cultures. 44 samples shares organoids, rna-seq
- GSE300722 Organoid modeling of lung branching morphogenesis and epithelial lineage specification [RNA-Seq] 40 samples shares epithelial, rna-seq
- GSE272476 Neutrophils exposed to a cholesterol metabolite secrete extracellular vesicles that promote epithelial-mesenchymal transition and stemness in breast cancer cells [RNA-seq] 30 samples shares epithelial, rna-seq
- GSE303852 Liver RNA-seq from obese mice following Roux-en-Y gastric bypass or sham surgery under chow or high-fat diet conditions 20 samples shares gastric, rna-seq
- GSE262879 Single-cell RNA-sequencing of murine pancreatic tumors derived from the orthotopic transplantation of Smad4 wild-type (WT) or Smad4 knockout (KO) pancreatic ductal adenocarcinoma (PDAC) KPC organoids in nu/nu mice. 18 samples shares organoids, rna-seq
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.