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Transcriptome analysis of liver tissue from patients with Autoimmune Hepatitis, Primary Biliary Cholangitis, and Chronic Hepatitis B

GSE304352 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2025/08/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 11 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
11 samples: 3 × Liver aspiration samples from PBC vs 3 × Liver aspiration samples from AIH vs 3 × Liver aspiration samples from CHB vs 2 × Liver aspiration samples from PBC&AIHGroups 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
Transcriptomic profiling of autoimmune hepatitis identifies TRAT1 as an in vitro negative regulator of NK cell effector functionsFrontiers in immunology · 2026
Summary (written by the submitters)
This study aims to identify immune-related genes in Autoimmune Hepatitis (AIH) by analyzing liver tissue transcriptomes. Bulk RNA sequencing was performed on liver biopsies from patients with AIH and two disease control groups: Primary Biliary Cholangitis (PBC) and Chronic Hepatitis B (CHB). Differential expression analysis was used to compare AIH against both control groups.
Read the full summary ↓
By intersecting the resulting differentially expressed genes (DEGs) with immune gene databases, we identified 19 common immune-related DEGs (IRDEGs). Gene Ontology (GO) analysis of these genes highlighted functions related to lymphocyte-mediated immunity and T-cell receptor signaling. This dataset provides a resource for exploring liver gene expression changes in AIH.
Published in
Transcriptomic profiling of autoimmune hepatitis identifies TRAT1 as an in vitro negative regulator of NK cell effector functions
Gao J, Huo L, Zhong J et al. · Frontiers in immunology 2026 · PMID 42483202 · doi:10.3389/fimmu.2026.1843865
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 GSE304352_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1300441 and SRA study SRP605890. Searching any of these in the dataset finder brings you back here.

Study design
3 × Liver aspiration samples from PBC vs 3 × Liver aspiration samples from AIH vs 3 × Liver aspiration samples from CHB vs 2 × Liver aspiration samples from PBC&AIH

Supports a between-group comparison across 11 samples.

How we read this: 4 replicated groups read from 11 sample titles; they account for 11 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.

Samples in this study
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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.