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Single-cell transcriptome of PBMC response to Omicron breakthrough infection

GSE248556 Homo sapiens (human) Single-cell RNA-seq 45 samples Submitted 2024/12/18 Platform GPL30173
At a glance

Single-cell RNA-seq · human · 45 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
45 samples: 35 distinct titles, 5 of them repeatedGroups 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 transcriptome atlas of peripheral immune features to Omicron breakthrough infection under booster vaccination strategiesFrontiers in immunology · 2024
Summary (written by the submitters)
To gain a deeper understanding of Omicron waves in the context of vaccination, we performed scRNA-seq together with single-cell V(D)J sequencing using PBMCs from nine Omicron breakthrough infection patients and six vaccinees to identify the possible cellular and molecular response mechanisms after breakthrough infection.
Published in
Single-cell transcriptome atlas of peripheral immune features to Omicron breakthrough infection under booster vaccination strategies
Zhang Y, Han S, Sun Q et al. · Frontiers in immunology 2024 · PMID 39835127 · doi:10.3389/fimmu.2024.1460442
This dataset
Open GSE248556 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 GSE248556_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 PRJNA1044775 and SRA study SRP474023. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39835127) ↗
Study design
35 distinct titles, 5 of them repeated
A_LC ×3 B_BI ×3 C_YT ×3 D_BIC ×3 E_BI ×3

How we read this: Read from 45 sample titles: 35 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

+ 5 more — browse all 45 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.