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Allergen Challenge for Evoked Phenotypes in Asthma (the ACE Study)

GSE250241 Homo sapiens (human) RNA-seq (gene expression) 66 samples Submitted 2024/03/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 66 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
66 samples: 66 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.
Paper
Epithelial miR-141 regulates IL-13-induced airway mucus productionJCI insight · 2021
Summary (written by the submitters)
This protocol outlines a single-site mechanistic study aiming to investigate long RNAs differentially expressed in the airway epithelium of asthma patients both at baseline and in response to segmental airway allergen challenges. Over approximately 14 days, the study spanned three visits: Visit 1: Comprehensive characterization of participants, encompassing lung function testing, methacholine challenge testing, and allergen skin prick testing.
Read the full summary ↓
Visit 2: Participants underwent bronchoscopy wherein three procedures were performed a. Epithelial brushings were performed in a segmental airway (baseline sample) b. Diluent (inactive control) was instilled into another segmental airway c. A small dose of allergen was administered into a third segmental airway using standardized cat or dust mite allergen extracts. Visit 3 (24 hours or 7 days post Visit 2): Another bronchoscopy was carried out to collect epithelial brushings in the diluent challenged and allergen challenged segments The collected epithelial brush samples underwent analysis for mRNA expression in the epithelial brushings. The study successfully incorporated a total of 23 subjects, which included 18 asthmatics (with stable or well-controlled conditions), 2 allergic non-asthmatics, and 3 non-allergic non-asthmatics.
Published in
Epithelial miR-141 regulates IL-13-induced airway mucus production
Siddiqui S, Johansson K, Joo A et al. · JCI insight 2021 · PMID 33682796 · doi:10.1172/jci.insight.139019
This dataset
Open GSE250241 in finder → Find more human 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 GSE250241_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 PRJNA1052718 and SRA study SRP478145. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 33682796) ↗
Study design
66 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 66 sample titles: 66 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

+ 26 more — browse all 66 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.