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The use of ectopic volar fibroblasts to modify skin identity III

GSE231997 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/09/09 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
16 samples: 16 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.
Paper
The use of ectopic volar fibroblasts to modify skin identityScience (New York, N.Y.) · 2024
Summary (written by the submitters)
The modification of skin identity, such as the conversion of residual limb/stump (non-volar) skin of amputees to pressure-resistant palmoplantar skin to enhance prosthesis use and minimize skin breakdown, has tremendous clinical potential. Recognizing the capacity of fibroblasts to modify keratinocyte differentiation, we hypothesized that volar fibroblast injections might induce ectopic volar characteristics.
Read the full summary ↓
First, we observed pressure-responsive volar fibroblast resulting in increased limb development after pressure treatment, then we confirmed this in using a bioprinted skin construct, and later in a clinical trial that showed increased volar measures in non-volar skin after volar fibroblast injections. Bulk and single cell RNA seq demonstrate gene ontology categories of cornified envelope, keratinization and morphogenic pathways. Thus, the long-term engraftment of volar fibroblasts creates a platform for the therapeutic development
Published in
The use of ectopic volar fibroblasts to modify skin identity
Lee SS, Sweren E, Dare E et al. · Science (New York, N.Y.) 2024 · PMID 39236183 · doi:10.1126/science.adi1650
This dataset
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.

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 GSE231997_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA970380 and SRA study SRP436550. Searching any of these in the dataset finder brings you back here.

Study design
16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 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.

Samples in this study
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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.