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Infants with perinatal HIV from the TARA cohort, pre-ART

GSE306003 Homo sapiens (human) Single-cell RNA-seq 32 samples Submitted 2025/08/21 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 32 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
32 samples: 32 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 role for Fas/FasL-dependent NK-mediated cytotoxicity in infants with perinatal HIViScience · 2025
Summary (written by the submitters)
This study investigated immune correlates of viral control in infants with perinatally acquired HIV prior to initiation of antiretroviral therapy (ART). Peripheral blood mononuclear cells (PBMC) were collected at a pre-ART time point and analyzed by single-cell RNA sequencing to profile immune cell composition and transcriptional states.
Read the full summary ↓
Infants were stratified into high and low viral load groups based on plasma HIV RNA levels at the time of sampling. Transcriptomic profiles were compared between groups to identify cell types, gene expression programs, and immune pathways associated with lower viral load, with the goal of defining candidate immune mechanisms that may contribute to spontaneous control of HIV replication in early life.
Published in
A role for Fas/FasL-dependent NK-mediated cytotoxicity in infants with perinatal HIV
Iyer A, de Armas L, Dinh V et al. · iScience 2025 · PMID 41210967 · doi:10.1016/j.isci.2025.113637
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 GSE306003_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 PRJNA1308862 and SRA study SRP610845. Searching any of these in the dataset finder brings you back here.

Study design
32 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 32 sample titles: 32 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
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