Single cell RNA-sequencing reveals molecular signatures that distinguish allergic from irritant contact dermatitis
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: 12 × CB vs 9 × PGroups 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 RNA Sequencing Reveals Molecular Signatures that Distinguish Allergic from Irritant Contact DermatitisThe Journal of investigative dermatology · 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 GSE267929_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 PRJNA1113649. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 21 samples.
How we read this: 2 replicated groups read from 21 sample titles; they account for 21 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.
- GSM8281713 CB17 CB
- GSM8281714 CB19 CB
- GSM8281715 CB20 CB
- GSM8281716 CB21 CB
- GSM8281717 CB22 CB
- GSM8281718 CB23 CB
- GSM8281719 CB27 CB
- GSM8281720 CB31 CB
- GSM8281721 CB43 CB
- GSM8281722 CB44 CB
- GSM8281723 CB46 CB
- GSM8281724 CB48 CB
- GSM8281725 P1 P
- GSM8281726 P2 P
- GSM8281727 P3 P
- GSM8281728 P4 P
- GSM8281729 P5 P
- GSM8281730 P6 P
- GSM8281731 P7 P
- GSM8281732 P8 P
- GSM8281733 P9 P
- GSE328391 Airway immune signatures of protection and disease progression in recent human tuberculosis household contacts [bulk RNA-seq] 125 samples shares signatures, contact
- GSE286042 Transcriptomic and Proteomic Signatures Following AS03-adjuvanted Influenza A/H7N9 Vaccine 1232 samples shares signatures
- GSE279480 Longitudinally stable T cell and innate immune activity distinguish healthy adult immunotypes I 1021 samples shares distinguish
- GSE280113 Progenitor effects and unique transcriptomic signatures linked to differentiation phenotype in clonally expanded antigen-specific CD8 T memory stem cells (TSCM) 509 samples shares signatures
- GSE315442 Transcriptomic profiling reveals distinct molecular signatures among lesion types in hidradenitis suppurativa 48 samples shares signatures
- GSE339456 Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [RNA-seq] 35 samples shares signatures
- GSE313307 Systemic infections alter cortical transcriptional signatures in Alzheimer′s disease 202 samples shares signatures
- GSE293805 Single nucleus RNA-sequencing atlas of pediatric solid tumors 182 samples shares rna-sequencing
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.