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Resolving the fibrotic niche of human liver cirrhosis using single-cell transcriptomics

GSE136103 Mus musculus (mouse) Single-cell RNA-seq 26 samples Submitted 2019/09/12 Platform GPL20301Platform GPL21103
At a glance

Single-cell RNA-seq · mouse · 26 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
26 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)
We profile the transcriptomes of over 100,000 human single cells, yielding molecular definitions for non-parenchymal cell types present in healthy and cirrhotic human liver. We uncover a novel scar-associated TREM2+CD9+ macrophage subpopulation, which expands in liver fibrosis, differentiates from circulating monocytes, has a corollary population in mouse liver fibrosis and is pro-fibrogenic.
Read the full summary ↓
We also define novel ACKR1+ and PLVAP+ endothelial cells which expand in cirrhosis, are topographically scar-restricted and enhance leucocyte transmigration. Multi-lineage ligand-receptor modelling of interactions between the novel scar-associated macrophages, endothelial cells and PDGFRα+ collagen-producing mesenchymal cells reveals intra-scar activity of several pro-fibrogenic pathways including TNFRSF12A, PDGFR and NOTCH signalling. Our work dissects unanticipated aspects of the cellular and molecular basis of human organ fibrosis at a single-cell level, and provides the conceptual framework required to discover rational therapeutic targets in liver cirrhosis.
This dataset
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.

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 GSE136103_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA561303 and SRA study SRP218975. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 26 more — browse all 26 samples with per-sample file links →

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