Single cell transcriptomes and spatial architecture of pancreatic pre-invasive lesions reveal acinar metaplastic cells' heterogeneity
Single-cell RNA-seq · mouse · 2 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 2 samples: 2 samples, each with a distinct title — no replicated groupsGroups 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
- Acinar Metaplastic Cells Generate Semi-Homogeneous Niches and Interact With Immune CellsGastroenterology · 2026
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 GSE274621_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 PRJNA1147296 and SRA study SRP525871. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 2 sample titles: 2 distinct titles with little repetition. 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.
- GSM8453700 7 months, MERFISH
- GSM8453701 7 months, scRNAseq
No close match found for this topic, so these are simply the most-viewed datasets of the same kind.
- GSE266690 Single cell approaches define neural stem cell niches and identify microglial ligands that enhance precursor-mediated remyelination 33 samples
- GSE241708 Genomic context sensitizes regulatory elements to genetic disruption 154 samples
- GSE237089 Non-CG DNA methylation and MeCP2 stabilize repeated tuning of long genes that distinguish closely related neuron types. 108 samples
- GSE273615 In vivo armed macrophages curb liver metastasis through tumor reactive T cell rejuvenation 36 samples
- GSE314329 Inflammatory Monocytes Constrain YAP-Induced Cell Proliferation 34 samples
- GSE102346 Regulation of m6A transcripts by the 3ʹ→5ʹ RNA helicase YTHDC2 is essential for a successful meiotic program in the mammalian germline 32 samples
- GSE60615 miRNAs in Treg-derived Exosomes 24 samples
- GSE260699 Spatially tuneable multi-omics sequencing using light-driven combinatorial barcoding of molecules in tissues 17 samples
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.