Systemic Inflammation Impairs Human Myelopoiesis [scRNA-Seq]
Single-cell RNA-seq · human · 18 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
- 18 samples: 18 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
- Systemic inflammation impairs myelopoiesis and interferon type I responses in humansNature immunology · 2025
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 GSE212092_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 PRJNA873948. 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 18 sample titles: 18 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.
- GSM6509143 Subject1_Day0_BM
- GSM6509144 Subject1_4h_BM
- GSM6509145 Subject1_Day7_BM
- GSM6509146 Subject2_Day0_BM
- GSM6509147 Subject2_4h_BM
- GSM6509148 Subject2_Day7_BM
- GSM6509149 Subject4_Day0_BM
- GSM6509150 Subject4_4h_BM
- GSM6509151 Subject4_Day7_BM
- GSM8579393 Subject1_Day0_PBMC
- GSM8579394 Subject1_4h_PBMC
- GSM8579395 Subject1_Day7_PBMC
- GSM8579396 Subject4_Day0_PBMC
- GSM8579397 Subject4_4h_PBMC
- GSM8579398 Subject4_Day7_PBMC
- GSM8579399 Subject5_Day0_PBMC
- GSM8579400 Subject5_4h_PBMC
- GSM8579401 Subject5_Day7_PBMC
- GSE292979 Characterisation of a pathogenic non-migratory fibroblast population in systemic sclerosis skin [scRNA-Seq] 15 samples shares scrna-seq, systemic
- GSE277476 Altered bone marrow myelopoiesis contributes to kidney injury [scRNA-seq] 11 samples shares myelopoiesis, scrna-seq
- GSE239775 Quantification of Systemic Inflammation by a Gene Score Uncovers Relevant Features on Acutely Decompensated Cirrhosis 1177 samples shares systemic
- GSE190564 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - whole tissue scRNA-Seq 62 samples shares scrna-seq
- GSE189754 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - CD45 scRNA-Seq 15 samples shares scrna-seq
- GSE256490 Single-cell atlas of the human brain vasculature across development, adulthood and disease (scRNA-Seq) 71 samples shares scrna-seq
- GSE278330 Systemic IL-23 blockade downregulates IL-23 receptor-expressing Type 17 T-cell subsets and upregulates regulatory gene expression in myeloid cells in human psoriasis skin 63 samples shares systemic
- GSE292828 Inhibition of NFAT after human uterus transplant promotes loss of tissue-resident NK cells and attendant pregnancy complications [scRNA-seq] 39 samples shares scrna-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.