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Mapping of transcription factor binding sites in mouse embryonic stem cells

GSE11431 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2008/06/12 Platform GPL9185
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 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
16 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)
Transcription factors and their specific interactions with targets are crucial in specifying gene expression programs. To gain insights into the transcriptional regulatory networks in embryonic stem cells, we use chromatin immunoprecipitation coupled to ultra-high-throughput DNA sequencing (ChIP-seq) to map the locations of thirteen sequence specific transcription factors (Nanog, Oct4, STAT3, Smad1, Sox2, Zfx, c-Myc, n-Myc, Klf4, Esrrb, Tcfcp2l1, E2f1 and CTCF) and two transcription regulators (p300 and Suz12).
Read the full summary ↓
These factors are known to play different roles in ES cell biology as components of the LIF and BMP signaling pathways, self-renewal regulators and key reprogramming factors. Our study provides insights into the integration of the signaling pathways to the ES cell-specific transcription circuitries. Intriguingly, we find specific genomic regions extensively targeted by different transcription factors. Collectively, the comprehensive mapping of transcription factor binding sites identifies important features of the transcriptional regulatory networks that define ES cell identity. Keywords: Transcription factor binding sites in undifferentiated mouse embryonic stem cells
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 GSE11431_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA106455 and SRA study SRP000217. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 16 more — browse all 16 samples with per-sample file links →

Datasets on a similar topic

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