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High-Throughput Transcriptomic Profiling for Bioactivity Screening: Mapping Molecular Targets and Potencies for Tox21 chemicals in HepaRG Cells 

GSE296254 Homo sapiens (human) RNA-seq (gene expression) Submitted 2026/05/31
At a glance

RNA-seq (gene expression) · human

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)
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)
This study used high-throughput transcriptomics (HTTr) to profile the concentration-dependent gene expression responses of ~300 reference chemicals with well-characterized mechanisms of action in differentiated HepaRG cells. The chemical set was selected to span a broad range of known molecular targets and biological response pathways.
Read the full summary ↓
Cells were exposed to each chemical in a 7-point concentration-response format (0.1?100 µM) for 24 hours, and transcriptomic changes were measured using the TempO-Seq human whole transcriptome version 2 (hWTv2) assay (~20,000 genes). The objective of this study was to develop a compendium of transcriptional profiles from mechanistically annotated reference chemicals to support interpretation of HTTr data from uncharacterized compounds. These profiles enable identification of gene expression signatures associated with specific molecular targets and pathways, and allow evaluation of concentration-dependent activation patterns across pathways. This dataset provides a foundation for linking chemical exposures to biological mechanisms, informing hazard characterization, and supporting predictive toxicology.  Keywords: Expression profiling by high throughput sequencing
This dataset
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.

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 GSE296254_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1254782 and SRA study SRP581122. Searching any of these in the dataset finder brings you back here.

Samples in this study

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