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The effect of CRISPLD2 on TGFβ-induced fibroblast fibrosis

GSE264288 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2024/04/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 40 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
40 samples: 40 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.
Summary (written by the submitters)
Systemic sclerosis (SSc) is an autoimmune connective tissue disease involving multiple organs. The most common clinical symptom of SSc is progressive fibrosis of the skin, and the pathologically manifestations of skin were activation and proliferation of fibroblasts and continuous proliferation of extracellular matrix. Transforming growth factor β (TGFβ) can promote the proliferation and activation of fibroblasts, causing excessive deposition of collagen and structural proteins, and thereby causing fibrosis and dysfunction of tissues and organs.
Read the full summary ↓
In this study, human cysteine-rich secreted protein LCCL domain protein 2 (CRISPLD2) was found increased reactivity in TGFβ induced fibroblasts, and we further confirmed that CRISPLD2 can participate in TGFβ induced fibroblast fibrosis from multiple perspectives and levels, and investigated the mechanism of CRISPLD2 in fibrosis, providing evidence for CRISPLD2 to become a clinical potential therapeutic target and a new biomarker.
This dataset
Open GSE264288 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 GSE264288_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 PRJNA1101875 and SRA study SRP502567. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
40 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 40 sample titles: 40 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
Datasets on a similar topic

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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.