Combustion products of burn pit constituents induce more changes in murine lungs with pre-existing asthma than naïve lungs
RNA-seq (gene expression) · mouse · 27 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
- 27 samples: 27 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
- Combustion products of burn pit constituents induce more changes in asthmatic than non-asthmatic murine lungsParticle and fibre toxicology · 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 GSE281365_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 PRJNA1183725 and SRA study SRP544160. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 27 sample titles: 27 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.
- GSM8619289 45_RNAseq Lung_HDM/CP
- GSM8619290 49_RNAseq Lung_HDM/CP
- GSM8619291 50_RNAseq Lung_HDM/SAL
- GSM8619292 52_RNAseq Lung_HDM/SAL
- GSM8619293 54_RNAseq Lung_HDM/SAL
- GSM8619294 57_RNAseq Lung_PBS/CP
- GSM8619295 58_RNAseq Lung_PBS/CP
- GSM8619296 59_RNAseq Lung_PBS/CP
- GSM8619297 61_RNAseq Lung_PBS/SAL
- GSM8619298 64_RNAseq Lung_PBS/SAL
- GSM8619299 66_RNAseq Lung_HDM/CP
- GSM8619300 67_RNAseq Lung_HDM/CP
- GSM8619301 72_RNAseq Lung_HDM/SAL
- GSM8619302 75_RNAseq Lung_PBS/CP
- GSM8619303 76_RNAseq Lung_PBS/CP
- GSM8619304 79_RNAseq Lung_PBS/SAL
- GSM8619305 80_RNAseq Lung_PBS/SAL
- GSM8619306 81_RNAseq Lung_PBS/SAL
- GSM8619307 96_RNAseq Lung_HDM/CP
- GSM8619308 97_RNAseq Lung_HDM/CP
- GSM8619309 98_RNAseq Lung_HDM/CP
- GSM8619310 99_RNAseq Lung_HDM/SAL
- GSM8619311 100_RNAseq Lung_HDM/SAL
- GSM8619312 101_RNAseq Lung_PBS/CP
- GSM8619313 102_RNAseq Lung_PBS/CP
- GSM8619314 104_RNAseq Lung_PBS/SAL
- GSM8619315 105_RNAseq Lung_PBS/SAL
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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.