Differential gene expression in Nintedanib-treated 3D skin rafts with Scleroderma (SSc) skin and healthy fibroblasts
RNA-seq (gene expression) · human · 30 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
- 30 samples: 10 × Patient vs 5 × HealthyGroups 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.
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 GSE289407_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: 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 PRJNA1222863 and SRA study SRP563469. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 20 samples read as cases, 10 as controls.
How we read this: 2 replicated groups read from 30 sample titles; they account for 15 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.
- GSM8790557 Patient 1 Patient
- GSM8790558 Patient 1+ Nintedanib
- GSM8790559 Patient 2 Patient
- GSM8790560 Patient 2+ Nintedanib
- GSM8790561 Healthy 1 Healthy
- GSM8790562 Healthy 1+ Nintedanib
- GSM8790563 Healthy 2 Healthy
- GSM8790564 Healthy 2+ Nintedanib
- GSM8790565 Patient 3 Patient
- GSM8790566 Patient 3+ Nintedanib
- GSM8790567 Patient 4 Patient
- GSM8790568 Patient 4+ Nintedanib
- GSM8790569 Patient 5 Patient
- GSM8790570 Patient 5+Nintedanib
- GSM8790571 Patient 6 Patient
- GSM8790572 Patient 6+Nintedanib
- GSM8790573 Healthy 3 Healthy
- GSM8790574 Healthy 3+ Nintedanib
- GSM8790575 Healthy 5 Healthy
- GSM8790576 Healthy 5+ Nintedanib
- GSM8790577 Healthy 6 Healthy
- GSM8790578 Healthy 6+ Nintedanib
- GSM8790579 Patient 7 Patient
- GSM8790580 Patient 7+Nintedanib
- GSM8790581 Patient 8 Patient
- GSM8790582 Patient 8+Nintedanib
- GSM8790583 Patient 9 Patient
- GSM8790584 Patient 9+Nintedanib
- GSM8790585 Patient 10 Patient
- GSM8790586 Patient 10+Nintedanib
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- GSE305928 Effect of latrunculin A on gene expression in human skin dermal fibroblasts 12 samples shares fibroblasts, skin
- GSE266852 Comparison of differential gene expression in blood PBMCs from healthy controls, patients with rheumatoid arthritis,and patients with lupus using single-cell transcriptome sequencing analysis. 10 samples shares differential, healthy
- GSE262112 Mechanical stretching of keloid and normal skin fibroblasts 20 samples shares fibroblasts, skin
- GSE330762 Kabuki syndrome type I fibroblast multi-omics dataset: bulk RNA-seq profiles from primary skin fibroblasts 19 samples shares fibroblasts, skin
- GSE231998 The use of ectopic volar fibroblasts to modify skin identity 49 samples shares fibroblasts, skin
- GSE272200 Differential gene expression in thalamic postmortem tissue of subjects with obsessive compulsive disorder 85 samples shares differential
- GSE294621 Vascular-type heterogeneity is associated with differential gene expression profiles of endothelial cells under shear stress 74 samples shares differential
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.