3D epigenomic landscape of human retinal pigment epithelium [RNA-seq]
RNA-seq (gene expression) · human · 8 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
- 8 samples: 4 × hRPE_RNA, vs 2 × iPSC-RPE_RNA, vs 2 × iPSC_RNA,Groups 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.
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 GSE307355_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 PRJNA1316331 and SRA study SRP617617. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 3 replicated groups read from 8 sample titles; they account for 8 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.
- GSM9222708 hRPE_RNA,rep1 hRPE_RNA,
- GSM9222709 hRPE_RNA,rep2 hRPE_RNA,
- GSM9222710 iPSC-RPE_RNA,rep1 iPSC-RPE_RNA,
- GSM9222711 iPSC-RPE_RNA,rep2 iPSC-RPE_RNA,
- GSM9222712 iPSC_RNA,rep1 iPSC_RNA,
- GSM9222713 iPSC_RNA,rep2 iPSC_RNA,
- GSM9883376 hRPE_RNA,rep3 hRPE_RNA,
- GSM9883377 hRPE_RNA,rep4 hRPE_RNA,
- GSE341236 3D epigenomic landscape of human retinal pigment epithelium 69 samples shares epigenomic, epithelium, retinal, pigment
- GSE307363 3D epigenomic landscape of human retinal pigment epithelium [CUT&Tag] 40 samples shares epigenomic, epithelium, retinal, pigment
- GSE242184 In vitro pigmentation of human iPSC-derived retinal pigment epithelium cells is not indicative of their quality for cell transplantation 4022 samples shares epithelium, retinal, pigment
- GSE267656 Efficient generation of human retinal pigment epithelium cells via chemically induced pluripotency 39 samples shares epithelium, retinal, pigment
- GSE271385 The APOE isoforms differentially shape the transcriptomic and epigenomic landscapes of human microglia in a xenotransplantation model of Alzheimer’s disease [RNA-seq] 19 samples shares epigenomic, rna-seq
- GSE328981 Quantum Molecular Resonance attenuates an oxidative stress-induced chimeric transcriptome program in human retinal pigment epithelial cells, preserving RNA structural fidelity 108 samples shares retinal, pigment
- GSE334500 Psychotropic-drug and neurotransmitter perturbation RNA-seq of human iPSC-derived cardiac and retinal organoids (ToxiPred) 96 samples shares retinal, rna-seq
- GSE309698 Transcriptomic Profiling of Bronchial Epithelium Reveals Dysregulated Interferon and Inflammatory Responses to Rhinovirus in Exacerbation-Prone Pediatric Asthma [RNA-Seq] 246 samples shares epithelium, rna-seq
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.