Exploring the Stability of Genomic Imprinting and X-Chromosome Inactivation in the Aged Brain (RNA-Seq)
RNA-seq (gene expression) · mouse · 11 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
- 11 samples: 11 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.
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 GSE232546_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 PRJNA972706 and SRA study SRP437724. 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 11 sample titles: 11 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.
- GSM7350031 999hcp MOUSE 1
- GSM7350032 1000hcp MOUSE 2
- GSM7350033 1084hcp MOUSE 3
- GSM7350034 1086hcp MOUSE 4
- GSM7350035 734hcp MOUSE 11
- GSM7350036 1619hcp MOUSE 5
- GSM7350037 1622hcp MOUSE 6
- GSM7350038 1678hcp MOUSE 7
- GSM7350039 1679hcp MOUSE 8
- GSM7350040 23971hcp MOUSE 10
- GSM7350041 1681hcp MOUSE 9
- GSE232548 Exploring the Stability of Genomic Imprinting and X-Chromosome Inactivation in the Aged Brain 83 samples shares x-chromosome, inactivation, imprinting, exploring, stability, brain, aged
- GSE295196 m6A RNA methylation in the maintenance of X-chromosome inactivation and X to autosome dosage compensation in early embryogenesis [RNA-Seq] 14 samples shares x-chromosome, inactivation, rna-seq
- GSE310108 SETDB1/HUSH modulates Xist RNA levels during establishment of X chromosome inactivation [RNA-Seq] 112 samples shares inactivation, rna-seq
- GSE286461 MAX inactivation deregulates the MYC network and induces neuroendocrine neoplasia in multiple tissues [RNA-seq] 46 samples shares inactivation, rna-seq
- GSE282784 X-chromosome upregulation operates on a gene-by-gene basis at RNA and protein levels [RNA-seq] 30 samples shares x-chromosome, rna-seq
- GSE236245 RNA-seq: The Interferon γ Pathway Enhances Pluripotency and X-Chromosome Reactivation in iPSC Reprogramming 24 samples shares x-chromosome, rna-seq
- GSE269251 Ehmt2 Inactivation in Pancreatic Epithelial Cells Shapes the Transcriptional Landscape and Inflammation Response of the Whole Pancreas [RNA-seq] 22 samples shares inactivation, rna-seq
- GSE319318 Inactivation of CDKN2A-ARF Promotes p53-Independent Remodeling of the PDAC Tumor Microenvironment [RNA-Seq] 20 samples shares inactivation, rna-seq
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.