Senescent Characteristics of Human Corneal Endothelial Cells upon Ultraviolet-A Exposure
RNA-seq (gene expression) · human · 12 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
- 12 samples: 4 × hCEnCs, Ctrl vs 4 × hCEnCs, I vs 4 × hCEnCs, UVAGroups 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
- Senescent characteristics of human corneal endothelial cells upon ultraviolet-A exposureAging · 2024
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 GSE250224_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 PRJNA1052700 and SRA study SRP478162. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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.
- GSM7975843 hCEnCs, Ctrl_1 hCEnCs, Ctrl
- GSM7975844 hCEnCs, Ctrl_2 hCEnCs, Ctrl
- GSM7975845 hCEnCs, Ctrl_3 hCEnCs, Ctrl
- GSM7975846 hCEnCs, Ctrl_4 hCEnCs, Ctrl
- GSM7975847 hCEnCs, IR_1 hCEnCs, I
- GSM7975848 hCEnCs, IR_2 hCEnCs, I
- GSM7975849 hCEnCs, IR_3 hCEnCs, I
- GSM7975850 hCEnCs, IR_4 hCEnCs, I
- GSM7975851 hCEnCs, UVA_1 hCEnCs, UVA
- GSM7975852 hCEnCs, UVA_2 hCEnCs, UVA
- GSM7975853 hCEnCs, UVA_3 hCEnCs, UVA
- GSM7975854 hCEnCs, UVA_4 hCEnCs, UVA
- GSE216842 Transcriptomic landscape of human primary stromal cells (fibroblasts, endothelial cells and mesenchymal stem cells) upon therapy-induced senescence (genotoxic chemotherapy） 24 samples shares endothelial, upon
- GSE323983 Senescence inhibition by rapamycin mitigates radiation-induced atherosclerotic characteristics in human coronary endothelial cells 23 samples shares characteristics, endothelial
- GSE285203 Transcriptome analyses of human corneal endothelial cell lines derived from patients with Fuchs Endothelial Corneal Dystrophy 11 samples shares endothelial, corneal
- GSE330283 Endothelial transcriptome remodeling by young and senescent MSCs depends on co-culture mode, ECM, and secreted factors 27 samples shares endothelial, senescent
- GSE311040 Multi-omics integrative approach of senescent endothelial cells and derived extracellular vesicles in a replicative senescence model 18 samples shares endothelial, senescent
- GSE284666 SenCat: Redefining human cell senescence through multiomic profiling of multiple senescent cell types 190 samples shares senescent
- GSE262619 Characteristics of Age-Associated Changes in the Whole Transcriptome of Human Peripheral Blood Leukocytes and Establishment of an Aging Clock 35 samples shares characteristics
- GSE275647 Role of Cancer-Associated Fibroblasts in Prognostic Stratification of Advanced-Stage Gastric Cancer through Interacting with Endothelial and Malignant Epithelial Cells [AGC RNA-seq] 216 samples shares endothelial
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.