Gene expression profiling at single nucleus level of microdissected white matter tissue samples of patients with progressive multiple sclerosis and non-neurological disease controls
RNA-seq (gene expression) · human · 15 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 15 samples: 15 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
- Single-Cell Multi-Omics Map of Cell Type-Specific Mechanistic Drivers of Multiple Sclerosis LesionsNeurology(R) neuroimmunology & neuroinflammation · 2024
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 GSE231585_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA967120 and SRA study SRP436074. 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 15 sample titles: 15 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.
- GSM7291242 C1_WM, snRNASeq
- GSM7291243 C3_WM, snRNASeq
- GSM7291244 C4_WM, snRNASeq
- GSM7291245 MS1_AL, snRNASeq
- GSM7291246 MS1_NAWM, snRNASeq
- GSM7291247 MS3_CA, snRNASeq
- GSM7291248 MS3_RL, snRNASeq
- GSM7291249 MS6_AL, snRNASeq
- GSM7291250 MS6_CA, snRNASeq
- GSM7291251 MS6_NAWM, snRNASeq
- GSM7291252 MS6_RL, snRNASeq
- GSM7291253 MS7_AL, snRNASeq
- GSM7291254 MS7_CA, snRNASeq
- GSM7291255 MS7_RL, snRNASeq
- GSM7291256 MS9_NAWM, snRNASeq
- GSE290554 Mapping the Molecular Signature of Progressive Multiple Sclerosis 94 samples shares progressive, sclerosis, multiple
- GSE290450 Mapping the Molecular Signature of Progressive Multiple Sclerosis [194017] 78 samples shares progressive, sclerosis, multiple
- GSE297192 Integrative single cell analysis of progressive multiple sclerosis induced neural stem cells reveals epigenetically dysregulated type-I-interferon signaling 25 samples shares progressive, sclerosis, multiple
- GSE327243 A CSF Disease-Associated Macrophage Signature defines Progressive Multiple Sclerosis [Frozen] 25 samples shares progressive, sclerosis, multiple
- GSE305477 Single-nucleus RNA-seq of peripheral blood mononuclear cells from multiple sclerosis patients and healthy controls 8 samples shares sclerosis, multiple, controls
- GSE231587 Progressive multiple sclerosis 32 samples shares progressive, sclerosis, multiple
- GSE279972 Foamy microglia link oxylipins to disease progression in multiple sclerosis 109 samples shares sclerosis, multiple
- GSE330029 Temporal changes in metabolism guide oligodendrocyte precursor cell dynamics in aging and multiple sclerosis [BulkRNAseq] 108 samples shares sclerosis, multiple
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.