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Maternal Vitamin C Deficiency and Genetic Risk Factors Contribute to Congenital Malformations through Dysregulation of DNA Methylation.

GSE295926 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 67 samples Submitted 2025/06/25 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 67 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
67 samples: 59 distinct titles, 7 of them repeatedGroups 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
Maternal Vitamin C Deficiency and Genetic Risk Factors Contribute to Congenital Defects through Dysregulation of DNA MethylationbioRxiv : the preprint server for biology · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Maternal Vitamin C Deficiency and Genetic Risk Factors Contribute to Congenital Defects through Dysregulation of DNA Methylation
van der Veer BK, Custers C, Brangers W et al. · bioRxiv : the preprint server for biology 2025 · PMID 40502204 · doi:10.1101/2025.05.27.656260
This dataset
Open GSE295926 in finder → Find more mouse methylation 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 GSE295926_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1256792 and SRA study SRP582123. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40502204) ↗
Study design
59 distinct titles, 7 of them repeated
RNA-E85-HF_B6_AAmin_female_TP159 ×3 WGBS-E85-HF_129_AAmin-norm_male_TP229 ×2 RNA-E85-HF_129_AAplus_female_TP160 ×2 RNA-E85-HF_129_AAplus_male_TP114 ×2 RNA-E85-HF_B6_AAmin_male_TP140 ×2 RNA-E85-HF_B6_AAplus_female_TP158 ×2 RNA-E85-HF_B6_AAplus_male_TP158 ×2

How we read this: Read from 67 sample titles: 59 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.

Samples in this study

+ 27 more — browse all 67 samples with per-sample file links →

Datasets on a similar topic

Search all mouse methylation datasets in GEO →

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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.