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Cerebral vascular transcriptome profiling reveals intermittent fasting modulates chronic cerebral hypoperfusion-induced disease pathways.

GSE246617 Mus musculus (mouse) RNA-seq (gene expression) 78 samples Submitted 2026/07/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 78 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
78 samples: 20 × BCIF vs 20 × SHAL vs 19 × BCAL vs 19 × SHIFGroups 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)
We investigated the effect of chronic cerebral hypoperfusion on transcriptomic changes in mouse cerebral arteries and whether intermittent fasting can modulate these transcriptomic changes.
This dataset
Open GSE246617 in finder → Find more mouse 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 GSE246617_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 PRJNA1033853 and SRA study SRP469333. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 × BCIF vs 20 × SHAL vs 19 × BCAL vs 19 × SHIF

Supports a between-group comparison across 78 samples.

How we read this: 4 replicated groups read from 78 sample titles; they account for 78 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

+ 38 more — browse all 78 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.