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Large scale cell-based transcriptome data treated with Jakyakgamcho-tang in HepG2 cell

GSE299063 Homo sapiens (human) RNA-seq (gene expression) 168 samples Submitted 2025/10/24 Platform GPL30209
At a glance

RNA-seq (gene expression) · human · 168 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
168 samples: 56 conditions, mostly in triplicateGroups 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
Multidimensional transcriptome dataset for systematic evaluation of Jakyakgamcho-tang-induced cell signaturesScientific data · 2026
Summary (written by the submitters)
Jakyakgamcho-tang (JGT) is the simplest form of herbal medicine composed of Paeoniae Radix (PR) and Glycyrrhizae Radix at Rhizoma (GR), and has been used to treat muscle-related diseases and inflammation. However, the pharmacological effects of JGT may vary depending on the ratio of the constituent herbs and the main preparation conditions of the extraction method.
Read the full summary ↓
Nevertheless, no gene expression dataset systematically reflecting these various variables has existed to date. In this study, a total of 498 transcriptome profiles were constructed with three concentrations and three replicates of RNA-seq data. It is structured to enable multidimensional analysis of the effects of various preparation conditions on gene expression by combining the ratio of PR:GR (2:1, 1:1, 1:2), solvent (water, 70% ethanol), and extraction method (combined decoction vs. separate decoction) of JGT, targeting three cell lines (HepG2, C2C12, and PC12). All raw and preprocessed data are deposited available through GEO, and standardized metadata and ingredient data are also provided. This dataset provides a foundation for exploring how traditional herbal medicine formulations affect cellular transcriptomic responses and can serve as a baseline for scientific optimization of herbal medicines.
Published in
Multidimensional transcriptome dataset for systematic evaluation of Jakyakgamcho-tang-induced cell signatures
Baek SJ, Lee H, Park SM et al. · Scientific data 2026 · PMID 41651870 · doi:10.1038/s41597-026-06759-6
This dataset
Open GSE299063 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 GSE299063_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 PRJNA1272494 and SRA study SRP590138. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41651870) ↗
Study design
56 conditions, mostly in triplicate
Wortmannin ×3 Vorinostat ×3 Trichostatin A ×3 JGW01 (500 ug/mL dose) ×3 JGW01 (100 ug/mL dose) ×3 JGW01 (20 ug/mL dose) ×3 JGW02 (500 ug/mL dose) ×3 JGW02 (100 ug/mL dose) ×3 +49 more

Supports a between-group comparison across 167 samples.

How we read this: 56 replicated groups read from 168 sample titles; they account for 167 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

+ 128 more — browse all 168 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.