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Transcriptomics profiling of lymphocytes from patients with resolved or chronic HBV infection

GSE233661 Homo sapiens (human) RNA-seq (gene expression) 71 samples Submitted 2024/05/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 71 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
71 samples: 71 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
A liver immune rheostat regulates CD8 T cell immunity in chronic HBV infectionNature · 2024
Summary (written by the submitters)
We generated transcriptional profiles of CD4 T cells, CD8 T cells, as well as a subset of CD 8 T cells that are specific for human hepatistis B virus core protein (HBcore or HBV_core) with bulk RNA sequencing. CD4 T cells are further stratified by PD1 expression profile (low or high).
Published in
A liver immune rheostat regulates CD8 T cell immunity in chronic HBV infection
Bosch M, Kallin N, Donakonda S et al. · Nature 2024 · PMID 38987588 · doi:10.1038/s41586-024-07630-7
This dataset
Open GSE233661 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 GSE233661_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: 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 PRJNA977249 and SRA study SRP440053. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38987588) ↗
Study design
71 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 71 sample titles: 71 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

+ 31 more — browse all 71 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.