CD4/CD8 ratio is associated with structural reorganization of vaccine-induced immune responses in people living with HIV
Single-cell RNA-seq · human · 60 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
- 60 samples: 60 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
- CD4/CD8 ratio is associated with structural reorganization of vaccine-induced immune responses in people living with HIVFrontiers in immunology · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE332711_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1465100 and SRA study SRP702242. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 60 sample titles: 60 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.
- GSM9752445 Pt3 H11 BCR-seq pre
- GSM9752446 Pt3 H11 scRNA-seq pre
- GSM9752447 Pt3 H11 TCR-seq pre
- GSM9752448 Pt10 H15 BCR-seq pre
- GSM9752449 Pt10 H15 scRNA-seq pre
- GSM9752450 Pt10 H15 TCR-seq pre
- GSM9752451 Pt7 H16 BCR-seq pre
- GSM9752452 Pt7 H16 scRNA-seq pre
- GSM9752453 Pt7 H16 TCR-seq pre
- GSM9752454 Pt4 H20 BCR-seq pre
- GSM9752455 Pt4 H20 scRNA-seq pre
- GSM9752456 Pt4 H20 TCR-seq pre
- GSM9752457 Pt5 H23 BCR-seq pre
- GSM9752458 Pt5 H23 scRNA-seq pre
- GSM9752459 Pt5 H23 TCR-seq pre
- GSM9752460 Pt6 H25 BCR-seq pre
- GSM9752461 Pt6 H25 scRNA-seq pre
- GSM9752462 Pt6 H25 TCR-seq pre
- GSM9752463 Pt9 H29 BCR-seq post
- GSM9752464 Pt9 H29 scRNA-seq post
- GSM9752465 Pt9 H29 TCR-seq post
- GSM9752466 Pt8 H37 BCR-seq post
- GSM9752467 Pt8 H37 scRNA-seq post
- GSM9752468 Pt8 H37 TCR-seq post
- GSM9752469 Pt7 H38 BCR-seq post
- GSM9752470 Pt7 H38 scRNA-seq post
- GSM9752471 Pt7 H38 TCR-seq post
- GSM9752472 Pt5 H42 BCR-seq post
- GSM9752473 Pt5 H42 scRNA-seq post
- GSM9752474 Pt5 H42 TCR-seq post
- GSM9752475 Pt3 H46 BCR-seq post
- GSM9752476 Pt3 H46 scRNA-seq post
- GSM9752477 Pt3 H46 TCR-seq post
- GSM9752478 Pt10 H47 BCR-seq post
- GSM9752479 Pt10 H47 scRNA-seq post
- GSM9752480 Pt10 H47 TCR-seq post
- GSM9752481 Pt4 H53 BCR-seq post
- GSM9752482 Pt4 H53 scRNA-seq post
- GSM9752483 Pt4 H53 TCR-seq post
- GSM9752484 Pt6 H59 BCR-seq post
+ 20 more — browse all 60 samples with per-sample file links →
- GSE285617 Characterization and effective expansion of CD4-CD8- TCRab+ T cells from individuals living with type 1 diabetes 24 samples shares cd4, cd8, living
- GSE322527 Single-cell transcriptomes and T cell receptor sequences of CD4 or CD8 single positive T lymphocytes from peripheral blood or urine of lupus nephritis patients at flare. 26 samples shares cd4, cd8
- GSE270651 Gene expression profile at single cell level of HIV-1 and HIV-2 specific CD8 T cells 17 samples shares cd8, hiv
- GSE280563 HIV-1 m6A methylome investigation by m6A-SAC-seq [CD4+ T cells] 12 samples shares cd4, hiv
- GSE328010 RNA sequencing of naïve, activated and HIV-1 infected CD4+ T cells 9 samples shares cd4, hiv
- GSE308745 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment.[PB cohort2] 87 samples shares cd4, cd8
- GSE254645 ACCELERATED CD8+ T CELL MATURATION IN INFANTS WITH PERINATAL HIV INFECTION 28 samples shares cd8, hiv
- GSE295601 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment. [P6] 18 samples shares cd4, cd8
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.