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Mechanism underlying long-term visual dysfunction in the mouse model of oxygen-induced retinopathy

GSE249919 Mus musculus (mouse) RNA-seq (gene expression) 2 samples Submitted 2024/12/31 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 2 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
2 samples
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.
Summary (written by the submitters)
To investigate the mechanism of long-term visual dysfunction in the mouse model of oxygen-induced retinopathy (OIR) by performing RNA sequencing (RNA-seq) . Then further verify the results in transcriptional, expression and function, to explore the methods to improve its electrophysiological function and provide new ideas for the treatment of retinopathy of prematurity (ROP).
Read the full summary ↓
7 days C57BL/6 mice were placed in a closed hyperoxia chamber. After 5 days, they were raised in the ordinary air environment. On, the 17th day and 25th day, the eyes were removed. The results of RNA-seq in the retina of the OIR mice at P17 showed that compared with the normal control group, 102 differentially expressed genes were identified, of which 95 were significantly up-regulated and 7 were significantly down-regulated. This study provides a new idea of neuroprotection for the treatment of patients with mild premature retinopathy.
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 GSE249919_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 PRJNA1051126 and SRA study SRP477510. Searching any of these in the dataset finder brings you back here.

Samples in this study

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