Cell type mapping reveals tissue niches and interactions in subcortical multiple sclerosis lesions [snRNA-seq]
Single-nucleus RNA-seq · human · 16 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
- Organism
- Homo sapiens (human)
- Samples
- 16 samples: 10 × brain, snRNA-seq multiple sclerosis, vs 6 × brain, snRNA-seq control,Groups 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
- Cell type mapping reveals tissue niches and interactions in subcortical multiple sclerosis lesionsNature neuroscience · 2024
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 GSE279180_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 PRJNA1171318 and SRA study SRP537712. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 2 replicated groups read from 16 sample titles; they account for 16 of them. 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.
- GSM8563681 brain, snRNA-seq control,1 brain, snRNA-seq contro…
- GSM8563682 brain, snRNA-seq control,2 brain, snRNA-seq contro…
- GSM8563683 brain, snRNA-seq control,3 brain, snRNA-seq contro…
- GSM8563684 brain, snRNA-seq control,4 brain, snRNA-seq contro…
- GSM8563685 brain, snRNA-seq control,5 brain, snRNA-seq contro…
- GSM8563686 brain, snRNA-seq control,6 brain, snRNA-seq contro…
- GSM8563687 brain, snRNA-seq multiple sclerosis, 1 brain, snRNA-seq multip…
- GSM8563688 brain, snRNA-seq multiple sclerosis, 2 brain, snRNA-seq multip…
- GSM8563689 brain, snRNA-seq multiple sclerosis, 3 brain, snRNA-seq multip…
- GSM8563690 brain, snRNA-seq multiple sclerosis, 4 brain, snRNA-seq multip…
- GSM8563691 brain, snRNA-seq multiple sclerosis, 5 brain, snRNA-seq multip…
- GSM8563692 brain, snRNA-seq multiple sclerosis, 6 brain, snRNA-seq multip…
- GSM8563693 brain, snRNA-seq multiple sclerosis, 7 brain, snRNA-seq multip…
- GSM8563694 brain, snRNA-seq multiple sclerosis, 8 brain, snRNA-seq multip…
- GSM8563695 brain, snRNA-seq multiple sclerosis, 9 brain, snRNA-seq multip…
- GSM8563696 brain, snRNA-seq multiple sclerosis, 10 brain, snRNA-seq multip…
- GSE301908 Single-cell spatial transcriptomic profiling defines a pathogenic inflammatory niche in chronic active multiple sclerosis lesions - snRNA-seq 17 samples shares sclerosis, snrna-seq, multiple, lesions
- GSE290554 Mapping the Molecular Signature of Progressive Multiple Sclerosis 94 samples shares sclerosis, multiple, mapping
- GSE290450 Mapping the Molecular Signature of Progressive Multiple Sclerosis [194017] 78 samples shares sclerosis, multiple, mapping
- 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
- GSE261258 Human regulatory memory B cells defined by expression of TIM-1 and TIGIT are dysfunctional in Multiple Sclerosis. 89 samples shares sclerosis, multiple
- GSE266132 Impact of the Multiple Sclerosis associated genetic variant CD226 Gly307Ser on human CD8 T cell functions 80 samples shares sclerosis, multiple
- GSE308103 Single-nucleus RNA-sequencing (snRNA-seq) analysis of normal lung tissues, precursor lung lesions and invasive lung adenocarcinomas 75 samples shares snrna-seq, lesions
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.