Live single-cell RNA-sequencing data from ALS donors only.
Single-cell RNA-seq · human · 21 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 21 samples: 21 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 transcriptomic landscape of the neuroimmune compartment in amyotrophic lateral sclerosis brain and spinal cordActa neuropathologica · 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 GSE204704_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 PRJNA841988 and SRA study SRP376866. 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 21 sample titles: 21 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.
- GSM6186103 ALS4 GM MA001 (ALS only)
- GSM6186104 ALS4 GM MA002 (ALS only)
- GSM6186105 ALS4 FN MA003 (ALS only)
- GSM6186106 ALS4 SC MA004 (ALS only)
- GSM6186107 ALS1 GM PM036 (ALS only)
- GSM6186108 ALS1 GM PM037 (ALS only)
- GSM6186109 ALS1 FN PM038 (ALS only)
- GSM6186110 ALS1 SC PM039 (ALS only)
- GSM6186111 ALS2 GM PM040 (ALS only)
- GSM6186112 ALS2 GM PM041 (ALS only)
- GSM6186113 ALS2 FN PM042 (ALS only)
- GSM6186114 ALS2 SC PM043 (ALS only)
- GSM6186115 ALS3 GM PM045 (ALS only)
- GSM6186116 ALS3 GM PM046 (ALS only)
- GSM6186117 ALS3 FN PM047 (ALS only)
- GSM6186118 ALS3 SC PM048 (ALS only)
- GSM6186119 ALS5 GM PM051 (ALS only)
- GSM6186120 ALS5 SC PM052 (ALS only)
- GSM6186121 ALS6 BA9+BA4+SC PM058 (ALS only)
- GSM6186122 ALS7 BA9+BA4+SC PM062 (ALS only)
- GSM6186123 ALS9 BA9+BA4+SC PM080 (ALS only)
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares als, single-cell, live
- GSE269877 Single-cell RNA-sequencing of BCG naïve and recurrent non-muscle invasive bladder cancer reveals a CD6/ALCAM-mediated immune-suppressive pathway 38 samples shares als, rna-sequencing, single-cell
- GSE326201 Single-cell RNA sequencing of human hepatocellular carcinoma and adjacent non-tumour liver tissues reveals etiology-associated and etiology-independent tumour microenvironmental features 18 samples shares als, single-cell, live
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares als, single-cell
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares als, single-cell
- GSE130970 Gene expression predicts histological severity and reveals distinct molecular profiles of nonalcoholic fatty liver disease 78 samples shares als, live
- GSE324131 A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis 38 samples shares als, single-cell
- GSE335480 Single-cell tracking reveals tumor-reactive T cell plasticity during melanoma TIL therapy 38 samples shares als, single-cell
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.