Single-cell profiling of blood and cerebrospinal fluid in tuberculous meningitis
Single-cell RNA-seq · human · 11 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
- 11 samples: 9 distinct titles, 1 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 profiling of blood and cerebrospinal fluid in tuberculous meningitisJournal of immunology (Baltimore, Md. : 1950) · 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 GSE285118_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 PRJNA1201202 and SRA study SRP553040. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 11 sample titles: 9 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.
- GSM8696926 TBM1_CSF
- GSM8696927 TBM1_PBMCs
- GSM8696928 TBM2_CSF
- GSM8696929 TBM2_PBMCs
- GSM8696930 TBM3_CSF
- GSM8696931 TBM3_PBMCs
- GSM8696932 TBM4_CSF
- GSM8696933 TBM4_PBMCs
- GSM8696934 Healthy-PBMCs
- GSM9009579 Healthy-PBMCs_02
- GSM9009580 Healthy-PBMCs_03
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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.