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Multiomic profiling of vascular endothelial cell differentiation from human embryonic stem cells [HUVEC RNA-Seq]

GSE328193 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2026/06/01 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 5 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
To investigate gene regulatory dynamics of normal endothelial cell (EC) differentiation at high resolution, an in vitro differentiation system was employed to derive functional vascular ECs from human embryonic stem cells. Human embryonic stem cells, mesodermal cells, and differentiating cells following VEGF-A stimulation at eight time points (1–48 hours), along with internal controls without VEGF-A treatment (referred to as non-ECs), were collected to profile global RNA expression and H3K27ac signals.
Read the full summary ↓
In addition, in situ Hi-C data were generated for ECs and non-ECs at 24 hours after VEGF-A treatment to characterize global chromatin contact profiles associated with the EC progenitor state.
This dataset
Open GSE328193 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 GSE328193_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 PRJNA1454100 and SRA study SRP692243. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in duplicate
HUVECs, RNA, control, ×2 HUVECs, RNA, ligands, ×2 HUVECs, RNA, ligands and cilengitide, ×2 HUVECs, RNA, knockdown control, ×2 HUVECs, RNA, ITGAV knockdown, ×2

Supports a case/control comparison: 2 samples read as cases, 2 as controls.

How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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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