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Lupus dermal fibroblasts hyper-respond to inflammatory cytokines and exhibit a pro-fibrotic phenotype to TGF-β in patients with scarring skin disease

GSE237690 Homo sapiens (human) RNA-seq (gene expression) 317 samples Submitted 2024/04/03 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 317 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
317 samples: 40 conditions, mostly with about 5 replicates eachGroups 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
Lupus dermal fibroblasts are proinflammatory and exhibit a profibrotic phenotype in scarring skin diseaseJCI insight · 2024
Summary (written by the submitters)
we examined responses to cytokines in dermal fibroblasts from the skin of SLE patients with CLE and healthy control volunteers to identify the inflammatory phenotype and gene expression profile associated with SLE and scarring CLE lesions.
Published in
Lupus dermal fibroblasts are proinflammatory and exhibit a profibrotic phenotype in scarring skin disease
Shoffner-Beck SK, Abernathy-Close L, Lazar S et al. · JCI insight 2024 · PMID 38358820 · doi:10.1172/jci.insight.173437
This dataset
Open GSE237690 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 GSE237690_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA996167 and SRA study SRP451611. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38358820) ↗
Study design
40 conditions, mostly with about 5 replicates each
1277-CD ×20 1323-CD ×20 1330-CD ×20 1377-CD ×20 739-CD ×20 796-CD ×20 997-CD ×20 212-CD ×19 +43 more

Supports a between-group comparison across 306 samples.

How we read this: 40 replicated groups read from 317 sample titles; they account for 306 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

+ 277 more — browse all 317 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.