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Transcriptional regulation of the main olfactory epithelium by environmental olfactory exposures

GSE327967 Mus musculus (mouse) Single-cell RNA-seq 34 samples Submitted 2026/07/24 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 34 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
34 samples: 26 distinct titles, 8 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
Transcriptional regulation of the main olfactory epithelium by environmental olfactory exposuresScientific reports · 2026
Summary (written by the submitters)
The main olfactory epithelium (MOE) is a highly heterogeneous tissue, comprised of many cell types including but not limited to olfactory sensory neurons, support cells, and immune cells. In this study, we investigated how environmental olfactory exposures impact cell-type specific transcriptional responses in the mouse MOE. We performed single-cell RNA sequencing (scRNA-seq) of the MOE following controlled environmental exposure to both well-known odorants (soiled bedding, amyl acetate) and an aeroallergen (house dust mite).
Read the full summary ↓
We identified major cell types and subtypes within the MOE and identified transcriptional changes in response to the olfactory exposures.
Published in
Transcriptional regulation of the main olfactory epithelium by environmental olfactory exposures
Haran V, Chu C, Owens RE et al. · Scientific reports 2026 · PMID 42463899 · doi:10.1038/s41598-026-62127-9
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 GSE327967_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1453408 and SRA study SRP691725. Searching any of these in the dataset finder brings you back here.

Study design
26 distinct titles, 8 of them repeated
F9 Pool ×2 F10 Pool ×2 F11 Pool ×2 F12 Pool ×2 M13 Pool ×2 M14 Pool ×2 M15 Pool ×2 M16 Pool ×2

How we read this: Read from 34 sample titles: 26 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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