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Single Nuclei RNA-Seq to map progression of non-alcoholic fatty liver disease (NAFLD) in patients II

GSE202379 Homo sapiens (human) Single-nucleus RNA-seq 59 samples Submitted 2024/04/04 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 59 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
59 samples: 59 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
Acquisition of epithelial plasticity in human chronic liver diseaseNature · 2024
Summary (written by the submitters)
Non-alcoholic fatty liver disease (NAFLD) is of increasing prevalence and concern. NAFLD can progress to non-alcoholic steatohepatitis (NASH), to cirrhosis and finally to end-stage liver disease where liver transplantation is required. We aimed to characterise this progression by performing single nuclei transcriptomic analysis of liver biopsies taken from patients across the disease spectrum. We have observed that hepatocytes are the cell type affected mostly by the disease and describe plasticity between cell types which may represent a regenerative process.
Published in
Acquisition of epithelial plasticity in human chronic liver disease
Gribben C, Galanakis V, Calderwood A et al. · Nature 2024 · PMID 38778114 · doi:10.1038/s41586-024-07465-2
This dataset
Open GSE202379 in finder → Find more human 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 GSE202379_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 PRJNA835824 and SRA study SRP374021. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38778114) ↗
Study design
59 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 59 sample titles: 59 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.

Samples in this study

+ 19 more — browse all 59 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.