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In vitro pigmentation of human iPSC-derived retinal pigment epithelium cells is not indicative of their quality for cell transplantation

GSE242184 Homo sapiens (human) Single-cell RNA-seq 4022 samples Submitted 2024/05/04 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 4022 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
4022 samples: 192 × iPS253-RPE, 6 weeks, rep1, cell vs 192 × iPS201-RPE, 6 weeks, rep1, cell vs 16 × Lonza-RPE, 6 weeks, rep1, cellGroups 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
Pigmentation level of human iPSC-derived RPE does not indicate a specific gene expression profileeLife · 2024
Summary (written by the submitters)
Retinal pigment epithelium (RPE) cells show heterogeneous level of pigmentation when cultured in vitro. We used Automated Live imaging and cell Picking System (ALPS) with single cell RNA sequencing (scRNA-seq) to analyze the correlation between color intensities and gene expression profiles of human-induced pluripotent stem (iPS) cell-derived RPE cells.
Published in
Pigmentation level of human iPSC-derived RPE does not indicate a specific gene expression profile
Nakai-Futatsugi Y, Jin J, Ogawa T et al. · eLife 2024 · PMID 38722314 · doi:10.7554/eLife.92510
This dataset
Open GSE242184 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 GSE242184_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1011919 and SRA study SRP458108. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38722314) ↗
Study design
192 × iPS253-RPE, 6 weeks, rep1, cell vs 192 × iPS201-RPE, 6 weeks, rep1, cell vs 16 × Lonza-RPE, 6 weeks, rep1, cell

Supports a between-group comparison across 400 samples.

How we read this: 3 replicated groups read from the first 400 of 4022 sample titles; they account for 400 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.

Samples in this study

+ 3982 more — browse all 4022 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.