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Transcriptome analysis of quiescent livers and regenerating livers after partial hepatectomy (PH) in young and aged mice

GSE282210 Mus musculus (mouse) RNA-seq (gene expression) 133 samples Submitted 2025/11/24 Platform GPL18480Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 133 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
Mus musculus (mouse)
Samples
133 samples: 129 distinct titles, 4 of them repeatedGroups 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
Differential Effects of Liver Regeneration on Aging-Related Changes in Gene Expression and Metabolic FunctionAging cell · 2025
Summary (written by the submitters)
To elucidate the effects of aging and the regeneration process on the liver, we conducted transcriptome analyses on young (11–14 weeks old), old (60 weeks old), and very old (100 weeks old) C57BL/6 mice (Clea Japan) before and after partial hepatectomy (PH), as well as on sham control mice.
Published in
Differential Effects of Liver Regeneration on Aging-Related Changes in Gene Expression and Metabolic Function
Murayama R, Horisawa K, Miura S et al. · Aging cell 2025 · PMID 40793865 · doi:10.1111/acel.70197
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 GSE282210_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 PRJNA1187589 and SRA study SRP545982. Searching any of these in the dataset finder brings you back here.

Study design
129 distinct titles, 4 of them repeated
YM_Ctrl_1X_mix ×2 OF_Ctrl_1X_mix ×2 VOM_52h_3X_mix ×2 VOM_Ctrl_1X_mix ×2

How we read this: Read from 133 sample titles: 129 distinct titles with little repetition. 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

+ 93 more — browse all 133 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.