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Epigenetic Switch Reshapes Epithelial Stem/Progenitor Cells Signatures and Contributes to Inflammatory Programming in Hidradenitis Suppurativa [scRNA-seq]

GSE226427 Homo sapiens (human) Single-cell RNA-seq 4 samples Submitted 2023/10/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 4 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
4 samples
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.
Summary (written by the submitters)
In this study, we used single-cell RNA-sequencing to reveal how cellular heterogeneity of Hidradenitis Suppurativa (HS) lesional epidermis was reshaped at the transcriptional level. By comparison with healthy interfollicular epidermal basal cells, in HS we revealed marked gene signatures centered on mitotic chromosome segregation, DNA replication and repair as well as cell-cell adhesion and chromatic remodeling.
Read the full summary ↓
Combing the pseudotime-ordered single-cell trajectory with the spatial localization analysis of defined basal cells, we further identified and validated a global alteration in cellular diversity within HS epidermis characterized by basal I-III cells hyperproliferation, concomitant decreases in superbasal keratinocytes, and phenotypic shifts toward the S100A cluster highly expressing pro-inflammatory genes S100A7/8/9. Cell-cell communication modeling suggested that HS BIII keratinocytes and S100A population serve as a crucial source to trigger IL-1 and IL-10 inflammatory cascades in the disease progression.
This dataset
Open GSE226427 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE226427_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA940167 and SRA study SRP425187. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38011564) ↗
Samples in this study

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+ 4 more — browse all 4 samples with per-sample file links →

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