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Single cell transcriptomics of cerebrospinal fluid cells from patients with recent-onset narcolepsy

GSE247134 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2024/12/31 Platform GPL30882Platform GPL18460Platform GPL24676
At a glance

Single-cell RNA-seq · human · 48 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
48 samples: 48 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.
Summary (written by the submitters)
Narcolepsy is a rare cause of excessive daytime sleepiness and may be associated or not with cataplexy, i.e. sudden muscle weakness. These forms are designated NAR-type 1 (NT1) and -type 2 (NT2), respectively. Notable characteristics of narcolepsy are that most patients carry the HLA-DQB1*06:02 allele and NT1-patients have highly decreased levels hypocretin-1 (synonym orexin-A) in the cerebrospinal fluid (CSF).
Read the full summary ↓
The pathogenesis of narcolepsy is still enigmatic but the strung HLA-bias and increased frequencies of CD4+ T cells reactive to hypocretin in the peripheral blood suggest autoimmune processes in the hypothalamus. Here we analyzed the transcriptomes of single CSF-cells from 16 narcoleptic patients by mRNAseq. As controls, we used single cells from patients with multiple sclerosis, radiologically isolated syndrome, and idiopathic intracranial hypertension. We identified 20 clusters of different cell types and >1000 genes that were differentially regulated between the different diseases. Surprisingly, the strongest upregulation in narcolepsy patients as compared to controls were the genome-encoded MTRNR2L12 and MTRNR2L8 peptides, which are homologous to mitochondria-encoded HUMANIN peptide that is known playing a role in other neurological diseases.
This dataset
Open GSE247134 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 GSE247134_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 PRJNA1036265. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 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

+ 8 more — browse all 48 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.