Single cell RNAseq of SOD1 mouse spinal cords
Single-cell RNA-seq · mouse · 12 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 12 samples: 4 × d120_WT_N vs 4 × d120_SOD1_veh_A vs 4 × d120_SOD1_RIPK1i_BGroups 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 transcriptomic and functional studies identify glial state changes and a role for inflammatory RIPK1 signaling in ALS pathogenesisImmunity · 2025
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 GSE287569_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 PRJNA1213761 and SRA study SRP558723. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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.
- GSM8748142 d120_WT_N4 d120_WT_N
- GSM8748143 d120_WT_N8 d120_WT_N
- GSM8748144 d120_SOD1_veh_A2 d120_SOD1_veh_A
- GSM8748145 d120_SOD1_veh_A5 d120_SOD1_veh_A
- GSM8748146 d120_SOD1_RIPK1i_B3 d120_SOD1_RIPK1i_B
- GSM8748147 d120_SOD1_RIPK1i_B4 d120_SOD1_RIPK1i_B
- GSM8748148 d120_WT_N9 d120_WT_N
- GSM8748149 d120_WT_N10 d120_WT_N
- GSM8748150 d120_SOD1_veh_A7 d120_SOD1_veh_A
- GSM8748151 d120_SOD1_veh_A11 d120_SOD1_veh_A
- GSM8748152 d120_SOD1_RIPK1i_B8 d120_SOD1_RIPK1i_B
- GSM8748153 d120_SOD1_RIPK1i_B12 d120_SOD1_RIPK1i_B
- GSE279899 RNA-Seq results of cervical spinal cords from NEAT1-KO; hSOD1G93A mice, compared to NEAT1-WT; hSOD1G93A 7 samples shares sod1, spinal, cords
- GSE288387 Bulk mRNAseq in control and Plp-CreER_Ddx20 cKO mouse spinal cords 12 samples shares spinal, cords
- GSE271662 RNA-seq of Mouse Spinal Cord after Lateral Compression Spinal Cord Injury followed by Delayed Atorvastatin or Vehicle Treatment [Bulk RNA-seq of mice spinal cords] 16 samples shares spinal, cords
- GSE224580 Transcriptomic analysis of the spinal cords of knock-in adult mice carrying the ATXN2/TDP-43 human transgenes 18 samples shares spinal, cords
- GSE244538 RNAseq of motor neurons with differential vulnerability to ALS isolated from the SOD1G93A mouse model of ALS 54 samples shares sod1
- GSE263048 RNA-seq of NSC-34 cells expressing SOD1 10 samples shares sod1
- GSE286267 The Role of the Thymus in ALS development in a SOD1 ALS model 76 samples shares sod1
- GSE318631 Sensory neuron dysfunction in dorsal root ganglia during disease onset in the SOD1G93A mouse model for ALS 6 samples shares sod1
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.