Exploring DNMT1 genome binding under homeostatic and hypomethylating conditions [ChIP-seq]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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
- Homo sapiens (human)
- Samples
- 12 samples: 12 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 GSE233726_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA977662 and SRA study SRP440173. 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 12 sample titles: 12 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.
- GSM7433282 ChIP-seq_MV4-11, gNT, Day 7 DMSO, DNMT1
- GSM7433283 ChIP-seq_MV4-11, gRNF4, Day 7 DMSO, DNMT1
- GSM7433284 ChIP-seq_MV4-11, gNT, Day 7 100nM GSK3685032, DNMT1
- GSM7433285 ChIP-seq_MV4-11, gRNF4, Day 7 100nM GSK3685032, DNMT1
- GSM7433286 ChIP-seq_MV4-11, gNT, Day 7 DMSO, H3K27ac
- GSM7433287 ChIP-seq_MV4-11, gRNF4, Day 7 DMSO, H3K27ac
- GSM7433288 ChIP-seq_MV4-11, gNT, Day 7 100nM GSK3685032, H3K27ac
- GSM7433289 ChIP-seq_MV4-11, gRNF4, Day 7 100nM GSK3685032, H3K27ac
- GSM7433290 ChIP-seq_MV4-11, gNT, Day 7 DMSO, Input
- GSM7433291 ChIP-seq_MV4-11, gRNF4, Day 7 DMSO, Input
- GSM7433292 ChIP-seq_MV4-11, gNT, Day 7 100nM GSK3685032, Input
- GSM7433293 ChIP-seq_MV4-11, gRNF4, Day 7 100nM GSK3685032, Input
- GSE297781 DNMT1 loss leads to hypermethylation of a subset of late replicating domains by DNMT3A (histone ChIP-seq) 14 samples shares dnmt1, chip-seq
- GSE297779 DNMT1 loss leads to hypermethylation of a subset of late replicating domains by DNMT3A (H3K36me2 native ChIP-seq) 8 samples shares dnmt1, chip-seq
- GSE284387 DNMT1 RFTS mutation alters RNA splicing and drives neurodegeneration via its RNA-binding function [RNA-Seq] 26 samples shares dnmt1, binding
- GSE290473 Exploring the Role of DNMT1 in RNA m⁵C Methylation (eCLIPseq II) 11 samples shares dnmt1, exploring
- GSE329512 SUMOylation enhances DNMT1 function to repress mega-intergenic RNAs and viral mimicry 19 samples shares dnmt1
- GSE329305 SUMOylation enhances DNMT1 function to repress mega-intergenic RNAs and viral mimicry [ChIP_WT-vs-CW-dTAG] 14 samples shares dnmt1
- GSE329304 SUMOylation enhances DNMT1 function to repress mega-intergenic RNAs and viral mimicry [ChIP_gUHRF1-and-WT-vs-RFTS] 13 samples shares dnmt1
- GSE298941 Discovery of a Novel DNMT1 Inhibitor with Improved Efficacy in Treating β-Thalassemia [ATAC-seq] 10 samples shares dnmt1
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.