Integrative CSF profiling identifies disease-specific immune responses in leptomeningeal disease
Single-cell RNA-seq · human · 42 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
- 42 samples: 42 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
- Integrative CSF profiling identifies disease-specific immune responses in leptomeningeal diseaseCell reports. Medicine · 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 GSE286518_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 PRJNA1209859 and SRA study SRP556948. 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 42 sample titles: 42 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.
- GSM8728771 Patient 1 CSF sample gene expression
- GSM8728772 Patient 2 CSF sample gene expression
- GSM8728773 Patient 3 CSF sample gene expression
- GSM8728774 Patient 4 CSF sample gene expression
- GSM8728775 Patient 5 CSF sample gene expression
- GSM8728776 Patient 6 CSF sample gene expression
- GSM8728777 Patient 7 first CSF sample gene expression
- GSM8728778 Patient 8 CSF sample gene expression
- GSM8728779 Patient 9 CSF sample gene expression
- GSM8728780 Patient 10 first CSF sample gene expression
- GSM8728781 Patient 11 CSF sample gene expression
- GSM8728782 Patient 12 first CSF sample gene expression
- GSM8728783 Patient 13 CSF sample gene expression
- GSM8728784 Patient 14 CSF sample gene expression
- GSM8728785 Patient 15 CSF sample gene expression
- GSM8728786 Patient 16 CSF sample gene expression
- GSM8728787 Patient 7 second CSF sample gene expression
- GSM8728788 Patient 10 second CSF sample gene expression
- GSM8728789 Patient 12 second CSF sample gene expression
- GSM8728790 Patient 12 third CSF sample gene expression
- GSM8728791 Patient 1 CSF sample TCR
- GSM8728792 Patient 2 CSF sample TCR
- GSM8728793 Patient 3 CSF sample TCR
- GSM8728794 Patient 4 CSF sample TCR
- GSM8728795 Patient 5 CSF sample TCR
- GSM8728796 Patient 6 CSF sample TCR
- GSM8728797 Patient 7 first CSF sample TCR
- GSM8728798 Patient 8 CSF sample TCR
- GSM8728799 Patient 9 CSF sample TCR
- GSM8728800 Patient 10 first CSF sample TCR
- GSM8728801 Patient 11 CSF sample TCR
- GSM8728802 Patient 12 first CSF sample TCR
- GSM8728803 Patient 13 CSF sample TCR
- GSM8728804 Patient 14 CSF sample TCR
- GSM8728805 Patient 15 CSF sample TCR
- GSM8728806 Patient 16 CSF sample TCR
- GSM8728807 Patient 7 second CSF sample TCR
- GSM8728808 Patient 10 second CSF sample TCR
- GSM8728809 Patient 12 second CSF sample TCR
- GSM8728810 Patient 12 third CSF sample TCR
+ 2 more — browse all 42 samples with per-sample file links →
- GSE279392 Single-cell RNA and TCR sequencing from skin, blood and cerebral spinal fluid (CSF) samples from Degos disease patients 116 samples shares csf
- GSE278723 Differential Roles of Astrocytic CSF1 in Alzheimer's Disease and Cerebral Amyloid Angiopathy: Insights from Transcriptomic Analysis 248 samples shares csf
- GSE286068 CITEseq analysis of human CSF cells in Multiple sclerosis 26 samples shares csf
- GSE327243 A CSF Disease-Associated Macrophage Signature defines Progressive Multiple Sclerosis [Frozen] 25 samples shares csf
- GSE308973 Localized PD-1 CAR T therapy reprograms neuroinflammation - human CSF data. 88 samples shares csf
- GSE295173 Multi-modal single-cell sequencing reveals network transition in circulating monocytes that aligns with faster recovery in trauma patients and favors a response to M-CSF [scRNA-Seq] 30 samples shares csf
- GSE292141 Single-cell elderly blood-CSF atlas implicates peripherally-influenced neuroinflammatory degeneration in normal pressure hydrocephalus 20 samples shares csf
- GSE181946 The PKCα/ZFP64/CSF1 Axis restricts Tumor Response to Anti-PD1 by driving Macrophage M2 Polarization in Hepatocellular Carcinoma [RNA-seq 1] 17 samples shares csf
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.