Spinal cord single-nuclei RNA sequencing of an EAE mouse model of multiple sclerosis
RNA-seq (gene expression) · mouse · 16 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
- Mus musculus (mouse)
- Samples
- 16 samples: 5 × BTKi EAE vs 4 × Vehicle naïve vs 4 × Vehicle EAE vs 3 × BTKi naïveGroups 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.
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 GSE281176_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 PRJNA1182672 and SRA study SRP543670. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 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.
- GSM8612249 Vehicle naïve 1 Vehicle naïve
- GSM8612250 Vehicle naïve 2 Vehicle naïve
- GSM8612251 Vehicle naïve 3 Vehicle naïve
- GSM8612252 Vehicle naïve 4 Vehicle naïve
- GSM8612253 BTKi naïve 1 BTKi naïve
- GSM8612254 BTKi naïve 2 BTKi naïve
- GSM8612255 BTKi naïve 3 BTKi naïve
- GSM8612256 Vehicle EAE 1 Vehicle EAE
- GSM8612257 Vehicle EAE 2 Vehicle EAE
- GSM8612258 Vehicle EAE 3 Vehicle EAE
- GSM8612259 Vehicle EAE 4 Vehicle EAE
- GSM8612260 BTKi EAE 1 BTKi EAE
- GSM8612261 BTKi EAE 2 BTKi EAE
- GSM8612262 BTKi EAE 3 BTKi EAE
- GSM8612263 BTKi EAE 4 BTKi EAE
- GSM8612264 BTKi EAE 5 BTKi EAE
- GSE281907 Spinal cord bulk RNA sequencing of an EAE mouse model of multiple sclerosis 16 samples shares eae, sclerosis, multiple, spinal, cord
- GSE304067 Single nuclei transcriptomics from lumbar spinal cord of EAE mice treated with MIF nuclease inhibitor PAANIB1 17 samples shares eae, spinal, cord
- GSE287324 Transcriptomic analysis of spinal cord in day 35 experimental autoimmune encephalomyelitis (EAE) model 10 samples shares eae, spinal, cord
- GSE283086 Distinct transcriptomic and epigenomic responses of mature oligodendrocytes during disease progression in a mouse model of multiple sclerosis [RNA-seq] 15 samples shares sclerosis, multiple
- GSE239700 NF-κB transcription factors RelA and c-Rel selectively control CD4+ T-cell function in multiple sclerosis and cancer [bulk_mouse] 12 samples shares sclerosis, multiple
- GSE326115 Metabolic and Skeletal Muscle Dysfunctions Correlate with Fatigue-Like Behavior in an Animal Model of Multiple Sclerosis 30 samples shares sclerosis, multiple
- GSE279705 Interferon-induced immunoproteasomes disturb neuronal metabolism and drive neurodegeneration in multiple sclerosis [RNA_Seq1_Proteasome] 18 samples shares sclerosis, multiple
- GSE300591 Temporal changes in metabolism guide oligodendrocyte precursor cell dynamics in aging and multiple sclerosis 15 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.