Single-cell RNA-seq reveals the keratinocyte heterogeneity and increased interfollicular basal keratinocytes in wound-induced hair follicle neogenesis
Single-cell RNA-seq · mouse · 6 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 6 samples: 6 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.
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 GSE308939_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 PRJNA1333457 and SRA study SRP625632. 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 6 sample titles: 6 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.
- GSM9256532 LW1, large wound
- GSM9256533 LW2, large wound
- GSM9256534 LW3, large wound
- GSM9256535 SW1, small wound
- GSM9256536 SW2, small wound
- GSM9256537 SW3, small wound
- GSE241109 Loss of the C-terminus of p63 leads to an increased expression of extracellular matrix genes in keratinocytes [RNA-seq] 14 samples shares keratinocytes, keratinocyte, increased
- GSE74534 Parallel single-cell bisulfite- and RNA-sequencing link transcriptional and epigenetic heterogeneity [RNA-seq] 96 samples shares heterogeneity, single-cell
- GSE269748 A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets 36 samples shares heterogeneity, single-cell
- GSE280067 Reprogramming of epidermal keratinocytes by PITX1 transforms the cutaneous cellular landscape and promotes wound healing [scRNA-seq] 36 samples shares keratinocytes, keratinocyte
- GSE302111 Biological processes in hind paw skin fibroblasts, keratinocytes and immune cells after PTX treatment (the short model) 35 samples shares keratinocytes, keratinocyte
- GSE41265 Single-cell transcriptomics reveals widespread heterogeneity in gene regulation and RNA processing in stimulated immune cells 24 samples shares heterogeneity, single-cell
- GSE220691 Kidney Single-Cell Atlas Reveals Macrophage Heterogeneity in Progression and Regression of Cisplatin Induced AKI. 22 samples shares heterogeneity, single-cell
- GSE239533 IKKα signaling in the nucleus or cytoplasm of keratinocytes leads to opposite skin phenotypes. 18 samples shares keratinocytes, keratinocyte
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.