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Transcriptomic Profiling of Bronchial Epithelium Reveals Dysregulated Interferon and Inflammatory Responses to Rhinovirus in Exacerbation-Prone Pediatric Asthma

GSE309705 Homo sapiens (human) RNA-seq (gene expression) 274 samples Submitted 2025/10/30 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 274 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
274 samples: 239 distinct titles, 35 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
Transcriptomic Profiling of Bronchial Epithelium Reveals Dysregulated Interferon and Inflammatory Responses to Rhinovirus in Exacerbation-Prone Pediatric AsthmabioRxiv : the preprint server for biology · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Transcriptomic Profiling of Bronchial Epithelium Reveals Dysregulated Interferon and Inflammatory Responses to Rhinovirus in Exacerbation-Prone Pediatric Asthma
Jayavelu ND, Benson B, Dela Cruz PC et al. · bioRxiv : the preprint server for biology 2025 · PMID 41279354 · doi:10.1101/2025.10.19.683298
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 GSE309705_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 PRJNA1336771 and SRA study SRP627948. Searching any of these in the dataset finder brings you back here.

Study design
239 distinct titles, 35 of them repeated
1_T ×2 3_T ×2 5_T ×2 6_T ×2 8_T ×2 15_T ×2 17_T ×2 26_T ×2 +27 more

How we read this: Read from 274 sample titles: 239 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

+ 234 more — browse all 274 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.