IL-13 decreases suceptibility to airway epithelial SARS-CoV-2 infection but increases disease severity in vivo
RNA-seq (gene expression) · mouse · 24 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
- Mus musculus (mouse)
- Samples
- 24 samples: 4 × lung epithelia, vehicle, noMAV, dono vs 4 × lung epithelia, IL13, noMAV, dono vs 4 × lung epithelia, vehicle,MAV, dono vs 4 × lung epithelia, IL13,MAV, donoGroups 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
- A predominately pulmonary activation of complement in a mouse model of severe COVID-19bioRxiv : the preprint server for biology · 2024
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 GSE249308_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 PRJNA1048487 and SRA study SRP475682. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 16 samples.
How we read this: 4 replicated groups read from 24 sample titles; they account for 16 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.
- GSM7933310 lung epithelia, vehicle, noMAV, donor1 lung epithelia, vehicle…
- GSM7933311 lung epithelia, vehicle, noMAV, donor2 lung epithelia, vehicle…
- GSM7933312 lung epithelia, vehicle, noMAV, donor3 lung epithelia, vehicle…
- GSM7933313 lung epithelia, vehicle, noMAV, donor4 lung epithelia, vehicle…
- GSM7933314 lung epithelia, IL13, noMAV, donor1 lung epithelia, IL13, n…
- GSM7933315 lung epithelia, IL13, noMAV, donor2 lung epithelia, IL13, n…
- GSM7933316 lung epithelia, IL13, noMAV, donor3 lung epithelia, IL13, n…
- GSM7933317 lung epithelia, IL13, noMAV, donor4 lung epithelia, IL13, n…
- GSM7933318 lung epithelia, vehicle,MAV, donor1 lung epithelia, vehicle…
- GSM7933319 lung epithelia, vehicle,MAV, donor2 lung epithelia, vehicle…
- GSM7933320 lung epithelia, vehicle,MAV, donor3 lung epithelia, vehicle…
- GSM7933321 lung epithelia, vehicle,MAV, donor4 lung epithelia, vehicle…
- GSM7933322 lung epithelia, IL13,MAV, donor1 lung epithelia, IL13,MA…
- GSM7933323 lung epithelia, IL13,MAV, donor2 lung epithelia, IL13,MA…
- GSM7933324 lung epithelia, IL13,MAV, donor3 lung epithelia, IL13,MA…
- GSM7933325 lung epithelia, IL13,MAV, donor4 lung epithelia, IL13,MA…
- GSM7933330 sublib1, 48samples
- GSM7933331 sublib2, 48samples
- GSM7933332 sublib3, 48samples
- GSM7933333 sublib4, 48samples
- GSM7933334 sublib5, 48samples
- GSM7933335 sublib6, 48samples
- GSM7933336 sublib7, 48samples
- GSM7933337 sublib8, 48samples
- GSE296513 Impaired AMPK Control of Alveolar Epithelial Cell Metabolism Promotes Pulmonary Fibrosis 45 samples shares epithelial
- GSE237767 Epithelial-Immune Metabolic Codependency Fuels Inflammatory Disease [Bulk RNA-seq] 34 samples shares epithelial
- GSE280817 Inflammation awakens dormant cancer cells by modulating epithelial-mesenchymal phenotypic state 20 samples shares epithelial
- GSE271300 A classical epithelial state drives acute resistance to KRAS inhibition in pancreas cancer 16 samples shares epithelial
- GSE226201 Gastric niche in the regulation of the epithelial cell differentiation in the human and mouse 83 samples shares epithelial
- GSE237772 Epithelial-Immune Metabolic Codependency Fuels Inflammatory Disease 38 samples shares epithelial
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.