Transcriptomic changes associated with SIRT1-based therapy in a model of retinal neurodegeneration
RNA-seq (gene expression) · mouse · 18 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
- 18 samples: 18 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
- SIRT1-based therapy targets a gene program involved in mitochondrial turnover in a model of retinal neurodegenerationScientific reports · 2025
Read the full summary ↓
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 GSE275359_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 PRJNA1150535 and SRA study SRP527774. 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 18 sample titles: 18 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.
- GSM8475526 Retina control1 (C1)
- GSM8475527 retina control 2 (C2)
- GSM8475528 Retina control3 (C3)
- GSM8475529 Retina EAE 1 (EAE1)
- GSM8475530 Retina EAE2 (EAE2)
- GSM8475531 Retina EAE3 (EAE3)
- GSM8475532 Retina EAE AAV-SIRT-1 (E-A-S1)
- GSM8475533 Retina EAE AAV-SIRT-2 (E-A-S2)
- GSM8475534 Retina EAE AAV-SIRT-3 (E-A-S3)
- GSM8475535 Reina EAE RSV-1 (E-R1)
- GSM8475536 Reina EAE RSV-2 (E-R2)
- GSM8475537 Reina EAE RSV-3 (E-R3)
- GSM8475538 Retina EAE SIRT1 KI 1 (E-S-KI1)
- GSM8475539 Retina EAE SIRT1 KI-2 (E-S-KI2)
- GSM8475540 Retina EAE SIRT1 KI-3 (E-S-KI3)
- GSM8475541 Reina SIRT1 KI-1 (S-KI1)
- GSM8475542 Reina SIRT1 KI-2 (S-KI2)
- GSM8475543 Reina SIRT1 KI-3 (S-KI3)
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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.