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Single-cell sequencing reveals NK cell dysregulation during chronic HIV infection and identifies transitional NK cell cytotoxicity related to HIV reservoir decay

GSE332837 Homo sapiens (human) Single-cell RNA-seq 39 samples Submitted 2026/07/22 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 39 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
39 samples: 39 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
Single-cell sequencing reveals NK cell dysregulation during chronic HIV infection and identifies transitional NK cell cytotoxicity related to HIV reservoir decayEBioMedicine · 2026
Summary (written by the submitters)
We performed scRNA-seq on NK cells from HCs and PLWH before/after ART. We identified ten subsets, including IFN-responding (c7) and proliferating (c8, c9) cells that expand in untreated PLWH. Cytotoxicity of the transitional NK before ART correlated with subsequent HIV-DNA decline. Our findings reveal NK cell heterogeneity during HIV infection, informing NK-based immunotherapies.
Published in
Single-cell sequencing reveals NK cell dysregulation during chronic HIV infection and identifies transitional NK cell cytotoxicity related to HIV reservoir decay
Cao WJ, Yang BP, Chen SY et al. · EBioMedicine 2026 · PMID 42475880 · doi:10.1016/j.ebiom.2026.106381
This dataset
Open GSE332837 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 GSE332837_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 PRJNA1469155. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42475880) ↗
Study design
39 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 17 samples read as cases, 5 as controls.

How we read this: Read from 39 sample titles: 39 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
Datasets on a similar topic

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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.