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Temporal multi-omics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation [RNA-seq]

GSE305933 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/12/08 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 10 × AK_RNAseq_hESCtoPHcellDifferentiation_Rep1_Day vs 10 × AK_RNAseq_hESCtoPHcellDifferentiation_Rep2_DayGroups 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
Temporal multiomics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiationScientific data · 2026
Summary (written by the submitters)
Human embryonic stem cells (hESCs) provide a powerful in vitro model to study lineage specification and the regulatory programs underlying early human development. Here, we present a high-resolution, temporal multi-omics dataset tracking mRNA, translation, and protein expression dynamics during hESC differentiation into definitive endoderm and subsequent polyhormonal (PH) cells, a key pancreatic lineage.
Read the full summary ↓
RNA-seq, ribosome profiling, and quantitative mass spectrometry-based proteomics were performed on matched samples collected at ten time points in biological duplicates, allowing detailed characterization of transcriptional, translational, and protein abundance changes over the differentiation timeline. The dataset exhibits high technical quality, with strong reproducibility between replicates and rigorous quality control metrics across all omics platforms. This extensive dataset provides critical insights into the complex regulatory mechanisms driving polyhormonal cell differentiation and serves as a valuable resource for the research community, enabling deeper exploration of mammalian development, endodermal lineage specification, and gene regulation.
Published in
Temporal multiomics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation
Keskin A, Shayya HJ, Patel A et al. · Scientific data 2026 · PMID 41545424 · doi:10.1038/s41597-026-06606-8
This dataset
Open GSE305933 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 GSE305933_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: 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 PRJNA1308481 and SRA study SRP610144. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41545424) ↗
Study design
10 × AK_RNAseq_hESCtoPHcellDifferentiation_Rep1_Day vs 10 × AK_RNAseq_hESCtoPHcellDifferentiation_Rep2_Day

Supports a between-group comparison across 20 samples.

How we read this: 2 replicated groups read from 20 sample titles; they account for 20 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
Datasets on a similar topic

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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.