Upper Airway Gene Expression in Hospitalized Children with Rhinovirus-induced Respiratory Illnesses
RNA-seq (gene expression) · human · 86 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
- 86 samples: 76 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
- Tuft cell cysteinyl leukotrienes are necessary for rhinovirus-induced mucus metaplasia, type 2 inflammation and airway hyperresponsiveness in immature miceFrontiers in immunology · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE311749_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1370873. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 86 sample titles: 76 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.
- GSM9331373 RVA_1, run 1
- GSM9331374 RVA_2, run 1
- GSM9331375 RVA_3, run 1
- GSM9331376 RVA_4, run 1
- GSM9331377 RVC_1, run 1
- GSM9331378 RVC_2, run 1
- GSM9331379 RVA_5, run 1
- GSM9331380 RVA_6, run 1
- GSM9331381 RVA_7, run 1
- GSM9331382 RVC_3, run 1
- GSM9331383 RVC_4, run 1
- GSM9331384 RVC_5, run 1
- GSM9331385 RVC_6, run 1
- GSM9331386 RVC_7, run 1
- GSM9331387 uninfected_1, run 1
- GSM9331388 uninfected_2, run 1
- GSM9331389 uninfected_3, run 1
- GSM9331390 uninfected_4, run 1
- GSM9331391 uninfected_5, run 1
- GSM9331392 uninfected_6, run 1
- GSM9331393 RSV_1, run 1
- GSM9331394 RSV_2, run 1
- GSM9331395 RSV_3, run 1
- GSM9331396 RSV_4, run 1
- GSM9331397 RSV_5, run 1
- GSM9331398 RSV_6, run 1
- GSM9331399 RSV_7, run 1
- GSM9331400 RSV_8, run 1
- GSM9331401 uninfected_1, run 2
- GSM9331402 uninfected_2, run 2
- GSM9331403 uninfected_3, run 2
- GSM9331404 RVC_8, run 1
- GSM9331405 RVC_9, run 1
- GSM9331406 RVC_10, run 1
- GSM9331407 RVC_11, run 1
- GSM9331408 RVC_12, run 1
- GSM9331409 RVC_13, run 1
- GSM9331410 RVC_14, run 1
- GSM9331411 RVA_8, run 1
- GSM9331412 RVC_15, run 1
+ 46 more — browse all 86 samples with per-sample file links →
- GSE156063 Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2 234 samples shares respiratory, illnesses, airway, upper
- GSE250448 RNA Sequencing Analysis of Monocytes Exposed to Airway Fluid from Children with Pediatric Acute Respiratory Distress Syndrome 61 samples shares respiratory, children, airway
- GSE318346 Small molecule-directed differentiation of submerged-cultured human nasal airway epithelia for respiratory disease modelling [bulkRNA-seq] 27 samples shares respiratory, airway
- GSE271148 Human airway submucosal gland organoids to study respiratory inflammation and infection [bulk RNA-seq] 16 samples shares respiratory, airway
- GSE271264 Human airway submucosal gland organoids to study respiratory inflammation and infection [bulk RNA-seq] 15 samples shares respiratory, airway
- GSE325412 Robust generation of distal respiratory airway organoids by an engineered cuboid chip to therapy chronic obstructive pulmonary disease 4 samples shares respiratory, airway
- GSE318347 Small molecule-directed differentiation of submerged-cultured human nasal airway epithelia for respiratory disease modelling [scRNA-seq] 3 samples shares respiratory, airway
- GSE271084 Human airway submucosal gland organoids to study respiratory inflammation and infection 2 samples shares respiratory, airway
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.