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IceQream: Quantitative chromosome accessibility analysis using physical TF models

GSE305339 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2025/08/24 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 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
10 samples: 3 × Mouse E7.5 gastrulation GEX vs 3 × Mouse E7.5 gastrulation ATACGroups 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
IceQream: Quantitative chromosome accessibility analysis using physical TF modelsNature communications · 2025
Summary (written by the submitters)
Single-cell mapping of chromosomal accessibility patterns has recently led to improved predictive modelling of epigenomic activity from sequence. However, quantitative models explaining the epigenome using directly interpretable components are still lacking. Here we develop IceQream (IQ), a modelling strategy and inference algorithm for regressing accessibility from sequences using physical models of transcription factor (TF) binding.
Read the full summary ↓
IQ uses spatial integration of sequences over a range of TF-DNA affinities and localization relative to the target locus. It infers TF effective concentrations as latent variables that activate or repress regulatory elements in a non-linear fashion. These are supplemented with synergistic and antagonistic pairwise interactions between TFs. Analysis of both human and mouse data shows that IQ derives similar, and in some cases, better performance compared to state-of-the-art deep neural network models. IQ provides an essential mechanistic and explicable baseline for further developments toward understanding gene and genome regulation from sequence.
Published in
IceQream: Quantitative chromosome accessibility analysis using physical TF models
Bercovich A, Lifshitz A, Eldar M et al. · Nature communications 2025 · PMID 41068106 · doi:10.1038/s41467-025-63925-x
This dataset
Open GSE305339 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE305339_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 PRJNA1305332 and SRA study SRP608632. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41068106) ↗
Study design
3 × Mouse E7.5 gastrulation GEX vs 3 × Mouse E7.5 gastrulation ATAC

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 6 of them. 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
Datasets on a similar topic

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