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Bulk RNA Sequencing of Wild Type and Cisplatin Induced AKI (3d and 7d groups) Mouse Kidney

GSE179806 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/07/01 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 9 samples, each with a distinct title — no replicated groupsGroups 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)
The study of transcriptome analyses using the Illumina HiSeq 4000 platform for renal tissue from three groups (Sham, 3 and 7 days after cisplatin induced AKI, n=3). In total, over 66.2 Gb clean reads were produced; Differentially expressed gene analysis identified 3984 and 2139 genes which were expressed higher or lower in cis3d group when compared to Sham group.
Read the full summary ↓
Among which, injury related genes, such as Havcr1, Lcn2, krt20 were significantly increased in cis3d group. On the other hand, the scale of different genes between cis7d and sham groups were greatly shrunk to 2144 (1564 up regulated and 580 down regulated). Accordingly, both the cell injury markers (krt20, lcn2 and havcr1) were markedly restored in cis7d group. In brief, the result of sham, cis3d and cis7d group shown the gene expression transition of injury pattern (progression stage) to repair pattern (regression stage) from 3 days to 7 days after acute injury of kidney tissue.
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 GSE179806_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 PRJNA745150 and SRA study SRP327638. Searching any of these in the dataset finder brings you back here.

Study design
9 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 9 sample titles: 9 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
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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.