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Analysis of transcription in peripheral blood mononuclear cells from HIV-infected patients receiving antiretroviral therapy

GSE297198 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/05/21 Platform GPL18460
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 11 × PBMC, before therapy, week 0, sampleGroups 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.
Summary (written by the submitters)
Human immunodeficiency virus is a cause of progressive infection leading to immune dysfunction. Although antiretroviral treatment can normalize the functional state of immune cells by reducing viral load, for some people the immune efficacy of antiretroviral therapy (ART) is insufficient. The aim of this study was to investigate the transcriptomic changes in peripheral blood mononuclear cells (PBMC) of patients receiving ART.
Read the full summary ↓
To evaluate the changes in PBMC, we conducted a clinical trial involving HIV-positive patients on ART. PBMC were collected before starting ART and after 24 weeks of treatment with ART along with estimation of viral load and CD4+ and CD8+ T-lymphocytes count. To evaluate the transcriptional profiles, we used RNA sequencing of isolated PBMC. The results showed two-fold differential expression of 70 genes in PBMC induced by ART and 56 genes prediction an increase in CD4+ lymphocytes after therapy. This information can be helpful for understanding molecular mechanisms of host response to ART.
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 GSE297198_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 PRJNA1262980 and SRA study SRP585258. Searching any of these in the dataset finder brings you back here.

Study design
11 × PBMC, before therapy, week 0, sample

Supports a between-group comparison across 11 samples.

How we read this: 1 replicated groups read from 20 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.