GEO series

A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure

GSE84133 Homo sapiens (human) Single-cell RNA-seq 6 samples Submitted 2016/09/26 Platform GPL17021Platform GPL16791

At a glance

Single-cell RNA-seq · human · 6 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: 6 samples
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.

Summary (written by the submitters)

While the function of the mammalian pancreas hinges on complex interactions of distinct cell types, gene expression profiles have primarily been described with bulk mixtures of cells. Here, we invoked inDrop, a droplet-based single-cell RNA-Seq method, to determine the transcriptomes of over 12,000 individual pancreatic cells from four human donors and two strains of mice.

Read the full summary ↓

Cells could be divided into 15 clusters that matched previously characterized cell types: all endocrine cell types, including rare ghrelin-expressing epsilon-cells, exocrine cell types, vascular cells, Schwann cells, quiescent and activated pancreatic stellate cells, and four types of immune cells. We detected subpopulations of ductal cells with distinct expression profiles, and validated their existence with immuno-histochemistry stains. Moreover, among human beta-cells, we detected heterogeneity in the regulation of genes relating to functional maturation and levels of ER-stress. Finally, we deconvolve bulk gene expression samples using single-cell RNA-Seq to detect disease associated differential expression. Thus, our cross-species dataset provides a resource for the discovery of novel cell type-specific and cell type-restricted transcription factors, signaling receptors, and medically-relevant genes.

This dataset

Open GSE84133 in finder → Find more RNA-seq datasets →

Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE84133_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA328774 and SRA study SRP078321. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27667365) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 6 more — browse all 6 samples with per-sample file links →

Datasets on a similar topic

GSE233906 Functional interrogation of lymphocyte subsets in alopecia areata using single-cell RNA sequencing 14 samples shares single-cell, inter
GSE306154 The Colon Contains an Immature/Intermediate iNKT Cell Population That is Expandable by CD1d Expressing Goblet Cells and Can be Protective in Colitis 9 samples shares population, inter
GSE293148 Metastasis-initiating osteosarcoma subpopulations establish paracrine interactions with both lung and tumor cells to create a metastatic niche 4 samples shares population, inter
GSE150672 Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology 438 samples shares single-cell
GSE284115 Single-cell transcriptomics of myeloid milieu reveals an angiogenic niche in triple-negative breast cancer 6 samples shares single-cell
GSE246613 Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer 266 samples shares single-cell
GSE263817 Comparative single-cell analysis reveals IFN-g as a driver of respiratory sequelae post COVID-19 33 samples shares single-cell
GSE38495 Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells 121 samples shares single-cell

Search all RNA-seq datasets in GEO →

Share this dataset

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.