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Gene expression analysis of nasal mucosa in birch pollen allergic and non-allergic individuals upon nasal provocation with birch pollen

GSE261239 Homo sapiens (human) RNA-seq (gene expression) 46 samples Submitted 2024/12/17 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 46 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
46 samples: 23 conditions, mostly in duplicateGroups 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
Transcriptomic Profiles of the Nasal Mucosa Following Birch Pollen Provocation Differ Between Birch Pollen-Allergic and Non-Allergic IndividualsAllergy · 2025
Summary (written by the submitters)
Birch pollen is a significant cause of allergic rhinitis, yet the mechanisms of sensitization is to be understood completely. Here, we investigate the changes in gene expression of birch pollen allergic and non-allergic individuals that occur as a result of nasal provocation with birch pollen.
Published in
Transcriptomic Profiles of the Nasal Mucosa Following Birch Pollen Provocation Differ Between Birch Pollen-Allergic and Non-Allergic Individuals
Sudharson S, Eckl-Dorna J, Meshcheryakova A et al. · Allergy 2025 · PMID 39717878 · doi:10.1111/all.16448
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 GSE261239_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 PRJNA1086145 and SRA study SRP494337. Searching any of these in the dataset finder brings you back here.

Study design
23 conditions, mostly in duplicate
TEB-001;N ×2 TEB-002;N ×2 TEB-003;N ×2 TEB-004;N ×2 TEB-007;N ×2 TEB-008;N ×2 TEB-009;N ×2 TEB-010;N ×2 +15 more

Supports a between-group comparison across 46 samples.

How we read this: 23 replicated groups read from 46 sample titles; they account for 46 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

+ 6 more — browse all 46 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.