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Pulmonary gene expression after ischemia reperfusion in young and old mice

GSE211951 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2024/04/06 Platform GPL24247
At a glance

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: 6 conditions, mostly with about 4 replicates eachGroups 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
Aging exacerbates murine lung ischemia-reperfusion injury by excessive inflammation and impaired tissue repair responseAmerican journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2024
Summary (written by the submitters)
To examine the age-related vulnerability to lung ischemia reperfusion injury, pulmonary gene expression profiles after lung ischemia reperfusion were compared between young and old mice.
Published in
Aging exacerbates murine lung ischemia-reperfusion injury by excessive inflammation and impaired tissue repair response
Hayasaka K, Ohkouchi S, Saito-Koyama R et al. · American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 2024 · PMID 37734444 · doi:10.1016/j.ajt.2023.09.004
This dataset
Open GSE211951 in finder → Find more mouse 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 GSE211951_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 PRJNA873042 and SRA study SRP394291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37734444) ↗
Study design
6 conditions, mostly with about 4 replicates each
old-1d ×4 old-1h ×4 old-sham ×4 young-1d ×4 young-1h ×4 young-sham ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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.

Samples in this study
Datasets on a similar topic

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