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Single-cell transcriptomic reconstruction of the human hair cycle: Capturing the temporal dynamics of skin tissue remodeling

GSE237520 Homo sapiens (human) Single-cell RNA-seq 22 samples Submitted 2025/07/31 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 22 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
22 samples: 7 × Skin_Donor A (40Y)_Single-hair region_Sample A vs 7 × Skin_Donor B (37Y)_Single-hair region_Sample B vs 5 × Skin_Donor C (36Y)_Single-hair region_Sample 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
Single-cell transcriptomic reconstruction of the human hair cycle: Capturing the temporal dynamics of skin tissue remodelingCell reports · 2025
Summary (written by the submitters)
To investigate dynamic molecular and cellular changes associated with skin tissue remodeling during the human hair cycle, we aimed to obtain single-cell RNA sequencing (scRNA-seq) data from different hair cycle phases. We obtained scRNA-seq from randomly dissected human skin samples containing a single hair. Nineteen small skin pieces with a single hair were dissected from three female donors (single-hair samples).
Read the full summary ↓
For comparison, we also collected three small skin pieces with no hairs from the same donors (non-hair samples). We enzymatically removed the interfollicular epidermis to focus our analysis on hair follicles and their surrounding dermis, which are the main areas of hair cycle-dependent tissue remodeling.
Published in
Single-cell transcriptomic reconstruction of the human hair cycle: Capturing the temporal dynamics of skin tissue remodeling
Yokota J, Gomi T, Harada Y et al. · Cell reports 2025 · PMID 40884793 · doi:10.1016/j.celrep.2025.116196
This dataset
Open GSE237520 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 GSE237520_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 PRJNA995574 and SRA study SRP449913. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40884793) ↗
Study design
7 × Skin_Donor A (40Y)_Single-hair region_Sample A vs 7 × Skin_Donor B (37Y)_Single-hair region_Sample B vs 5 × Skin_Donor C (36Y)_Single-hair region_Sample C

Supports a between-group comparison across 19 samples.

How we read this: 3 replicated groups read from 22 sample titles; they account for 19 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
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