Single-cell RNA-seq data of human PBMC from amyotrophic lateral sclerosis patients
Single-cell RNA-seq · human · 40 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
- 40 samples: 30 × ALS vs 10 × CGroups 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
- Th17 and effector CD8 T cells relate to disease progression in amyotrophic lateral sclerosis: a case control studyJournal of neuroinflammation · 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 GSE244263_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 PRJNA1022022 and SRA study SRP463782. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 2 replicated groups read from 40 sample titles; they account for 40 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.
- GSM7810083 ALS_3 ALS
- GSM7810084 ALS_6 ALS
- GSM7810085 ALS_7 ALS
- GSM7810086 ALS_8 ALS
- GSM7810087 ALS_9 ALS
- GSM7810088 ALS_10 ALS
- GSM7810089 ALS_11 ALS
- GSM7810090 ALS_13 ALS
- GSM7810091 ALS_14 ALS
- GSM7810092 ALS_16 ALS
- GSM7810093 ALS_17 ALS
- GSM7810094 ALS_18 ALS
- GSM7810095 ALS_19 ALS
- GSM7810096 ALS_20 ALS
- GSM7810097 ALS_21 ALS
- GSM7810098 ALS_22 ALS
- GSM7810099 ALS_23 ALS
- GSM7810100 ALS_24 ALS
- GSM7810101 ALS_25 ALS
- GSM7810102 ALS_26 ALS
- GSM7810103 ALS_27 ALS
- GSM7810104 ALS_28 ALS
- GSM7810105 ALS_29 ALS
- GSM7810106 ALS_30 ALS
- GSM7810107 ALS_31 ALS
- GSM7810108 ALS_32 ALS
- GSM7810109 ALS_33 ALS
- GSM7810110 ALS_34 ALS
- GSM7810111 ALS_35 ALS
- GSM7810112 ALS_36 ALS
- GSM7810113 C_1 C
- GSM7810114 C_2 C
- GSM7810115 C_3 C
- GSM7810116 C_4 C
- GSM7810117 C_5 C
- GSM7810118 C_6 C
- GSM7810119 C_7 C
- GSM7810120 C_8 C
- GSM7810121 C_9 C
- GSM7810122 C_10 C
- GSE227835 Single-cell RNA-seq data of human PBMC from Myasthenia Gravis patients 40 samples shares pbmc, single-cell, rna-seq
- GSE267023 scRNA-seq analysis of PBMCs from ischemic stroke patients 16 samples shares pbmc, rna-seq
- GSE279945 OP3: single-cell multimodal dataset in PBMCs for perturbation prediction benchmarking 102 samples shares pbmc, single-cell
- GSE327167 Single-cell RNA-seq profiling of pleural mesothelioma and comparator pleural specimens 113 samples shares single-cell, rna-seq
- GSE318490 Single-cell RNA-seq of tumor samples from six advanced HGSOC patients across treatment stages (pre-NACT, post-NACT and platinum-sensitive recurrence) 10 samples shares single-cell, rna-seq
- GSE287301 Single-cell RNA-sequencing of HNSCC-infiltrating T cells 48 samples shares single-cell, rna-seq
- 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 single-cell, rna-seq
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares single-cell, rna-seq
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.