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Single-cell transcriptomic analysis identifies infiltrating plasmacytoid dendritic cells in psoriasis epidermis

GSE254707 Homo sapiens (human) Single-cell RNA-seq 4988 samples Submitted 2024/06/25 Platform GPL21697
At a glance

Single-cell RNA-seq · human · 4988 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
4988 samples: 213 × Psoriasis_PP vs 187 × Psoriasis_PNGroups 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.
Summary (written by the submitters)
The study focuses on the cellular composition of the psoriasis epidermis, using single-cell transcriptomics to identify cell subsets and their interactions in both healthy and psoriatic skin. The research uncovers three keratinocyte populations and seven immune cell subsets exclusive to psoriatic lesions. A significant finding is the identification of a previously undetected population of plasmacytoid dendritic cells (pDCs) in the psoriatic epidermis, suggesting their role in the disease's pathogenesis.
Read the full summary ↓
The study also highlights enhanced keratinocyte-immune cell interactions in psoriatic lesions, contributing to our understanding of psoriasis at the cellular level.
This dataset
Open GSE254707 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 GSE254707_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 PRJNA1071557 and SRA study SRP487156. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
213 × Psoriasis_PP vs 187 × Psoriasis_PN

Supports a between-group comparison across 400 samples.

How we read this: 2 replicated groups read from the first 400 of 4988 sample titles; they account for 400 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.

Samples in this study

+ 4948 more — browse all 4988 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.