Identification of IPF Specific Genes Expressed by Lung Tissue - Derived Fibroblasts Using Next Generation Sequencing
RNA-seq (gene expression) · human · 43 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
- 43 samples: 43 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
- Identification of IPF specific genes expressed by lung tissue-derived fibroblasts using next generation sequencingSarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2026
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 GSE301181_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 PRJNA1284232 and SRA study SRP596067. 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 43 sample titles: 43 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.
- GSM9076829 IPF24_12030
- GSM9076830 IPF28_726449
- GSM9076831 IPF11_48887
- GSM9076832 IPF32_884290
- GSM9076833 IPF16_569111
- GSM9076834 IPF33_200269
- GSM9076835 IPF2_736446
- GSM9076836 IPF18_571055
- GSM9076837 IPF19_571055
- GSM9076838 NC2_498248
- GSM9076839 IPF8_597484
- GSM9076840 NC3_237538
- GSM9076841 IPF13_499601
- GSM9076842 IPF26_596026
- GSM9076843 IPF9_62426
- GSM9076844 IPF14_39654
- GSM9076845 IPF30_825861
- GSM9076846 NC6_163088
- GSM9076847 IPF27_771852
- GSM9076848 NC7_554682
- GSM9076849 IPF25_745115
- GSM9076850 IPF12_436629
- GSM9076851 IPF20_579446
- GSM9076852 IPF5_799551
- GSM9076853 IPF7_472236
- GSM9076854 IPF6_535121
- GSM9076855 IPF23_706027
- GSM9076856 NC9_430110
- GSM9076857 NC10_475046
- GSM9076858 IPF15_552407
- GSM9076859 IPF4_512140
- GSM9076860 IPF17_568540
- GSM9076861 IPF10_212249
- GSM9076862 IPF3_732703
- GSM9076863 IPF29_704403
- GSM9076864 IPF31_850944
- GSM9076865 IPF1_569464
- GSM9076866 IPF21_604261
- GSM9076867 NC1_557648
- GSM9076868 NC4_340692
+ 3 more — browse all 43 samples with per-sample file links →
- GSE92592 mRNA Sequencing of Ideopathic Pulmonary Fibrosis (IPF) and Control Samples from the Lung Tissue Research Consortium (LTRC) 39 samples shares ipf, lung
- GSE286182 Single Nuclear RNAseq and MultiOme of IPF and Control Lung Tissue 75 samples shares ipf, lung
- GSE255626 Next generation sequencing from primary glioblastoma patient tissues (Total RNA-seq) 109 samples shares generation, next
- GSE319124 Next-GenerationPediatric Cancer Models: Patient-Matched Orthotopic Xenografts, 3D Organoids, 2D Cultures, and Cell Lines for Identification of Therapeutic Vulnerabilities in Pediatric Solid Tumors [scRNAseq] 59 samples shares generation, next
- GSE273882 Arginine Promotes The Activation of Human Lung Fibroblasts Independent of Its Metabolism 52 samples shares fibroblasts, lung
- GSE267498 Generation of hiPSC-derived brain microvascular endothelial cells using a combination of directed differentiation and transcriptional reprogramming strategies 37 samples shares generation, derived
- GSE223075 Next Generation Sequencing facilitates to identify the differential expression genes of sorted conventional CD8+ T cells and MAIT cells 35 samples shares generation, next
- GSE275145 Creeping fat-derived mechanosensitive fibroblasts drive intestinal fibrosis in Crohn’s disease strictures [Human scRNA-seq] 29 samples shares fibroblasts, derived
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.