Longitudinal single-cell transcriptomics of monocytes, Tfh and gd Tcells following a control human malaria infection.
Single-cell RNA-seq · human · 16 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
- 16 samples: 16 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
- Tfh2 and a subset of Tfh1 cells associate with antibody-mediated immunity to malariaJCI insight · 2025
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 GSE253661_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 PRJNA1066724 and SRA study SRP484709. 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 16 sample titles: 16 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.
- GSM8024711 monocyte day 0 pre-infection
- GSM8024712 monocyte day 8 post-infection
- GSM8024713 monocyte day 16 post-infection
- GSM8024714 monocyte day 36 post-infection
- GSM8024715 tfh day 0 pre-infection
- GSM8024716 tfh day 8 post-infection
- GSM8024717 tfh day 16 post-infection
- GSM8024718 tfh day 36 post-infection
- GSM8024719 gd day 0 pre-infection
- GSM8024720 gd day 8 post-infection
- GSM8024721 gd day 16 post-infection
- GSM8024722 gd day 36 post-infection
- GSM8437028 TCR_tfh day 0 pre-infection
- GSM8437029 TCR_tfh day 8 post-infection
- GSM8437030 TCR_tfh day 16 post-infection
- GSM8437031 TCR_tfh day 36 post-infection
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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.