Chromatin Analysis Services for Epigenetics Research
Chromatin analysis encompasses a suite of technologies that interrogate how DNA is packaged, regulated, and organized within the nucleus. These methods enable researchers to map protein–DNA interactions, profile open chromatin regions, and reconstruct three-dimensional genome architecture — providing mechanistic insight into gene regulation, cellular differentiation, and disease pathogenesis. At CD Genomics, we offer an integrated chromatin analysis platform covering the full spectrum of epigenomic approaches, from classical ChIP-seq to single-cell ATAC-seq and Hi-C.
Key Highlights of Our Chromatin Analysis Portfolio:
Multi-Technology Platform: ChIP-seq, ATAC-seq, CUT&Tag, Hi-C, CUT&RUN, DAP-seq, and more — all under one service umbrella.
End-to-End Support: From experimental design and sample preparation through publication-ready bioinformatics and custom visualization.
Challenging Sample Expertise: Optimized protocols for low-input material, FFPE tissues, and non-model organisms across plant and animal species.
Rigorous Quality Control: Multi-point QC checkpoints including FRiP, TSS enrichment, library complexity, and peak reproducibility for every project.
Chromatin analysis is central to modern epigenetics research. By mapping how DNA interacts with histones, transcription factors, and structural proteins, researchers can uncover the regulatory mechanisms that control gene expression in development, disease, and across species. Our integrated service platform delivers the full spectrum of chromatin analysis capabilities across six technology categories, with rigorous quality control at every stage and bioinformatics support designed for publication-ready results.
Chromatin immunoprecipitation sequencing (ChIP-seq) remains the most widely used method for genome-wide mapping of histone modifications, transcription factors, and other chromatin-associated proteins. The assay uses a specific antibody to enrich protein-bound DNA fragments, which are then sequenced to identify binding sites across the genome. Our ChIP-Seq service covers both narrow peak (transcription factors) and broad domain (repressive histone marks) analysis.
For researchers working with limited cell numbers, CUT&Tag (Cleavage Under Targets and Tagmentation) offers a streamlined alternative. By using a protein A–Tn5 fusion to directly tag target-bound DNA, CUT&Tag achieves higher signal-to-noise ratios than ChIP-seq while requiring significantly fewer cells. Our CUT&Tag service is particularly well suited for histone modification profiling of active chromatin marks. CUT&RUN (Cleavage Under Targets and Release Using Nuclease) provides an intermediate option with lower accessibility bias than CUT&Tag and reliable detection of both transcription factors and histone modifications. Our CUT&RUN service is recommended when a balanced profile across active and repressed chromatin is required.
Chromatin Accessibility — ATAC-Seq & scATAC-Seq
ATAC-seq uses a hyperactive Tn5 transposase to fragment and tag DNA in open chromatin regions, identifying active promoters, enhancers, and regulatory elements. Single-cell ATAC-seq enables profiling at cellular resolution for heterogeneous tissues. See our ATAC-Seq and scATAC-Seq service pages.
3D Genome Architecture — Hi-C Family
Hi-C captures genome-wide chromatin conformation, revealing A/B compartments, TADs, and chromatin loops. We offer Hi-C, Capture Hi-C, Micro-C XL for nucleosome-resolution, and HiChIP for protein-centric interaction profiling.
RNA-Centric Chromatin Interaction
ChIRP-Seq & ChIRP-MS identify genomic binding sites and protein interactors of lncRNAs. eCLIP-seq maps RNA-protein interactions at nucleotide resolution. Also available: ssDRIP-Seq (R-loop mapping), DRIPc-seq, and PIRCh-seq.
Selecting the appropriate chromatin analysis method depends on your biological question, sample availability, and the resolution needed. The table below summarizes key considerations across our technology portfolio.
Method
Biological Question
Typical Sample Input
Antibody Required
Sequencing Depth
Signal-to-Noise
Best For
ChIP-Seq
Where does a specific protein bind to DNA?
Standard to high
Yes
10–50 M reads
Moderate
Histone marks, TFs; repressive marks preferred
ATAC-Seq
Where is chromatin open/accessible?
Moderate to high
No
50 M reads
High
Open chromatin, regulatory elements
CUT&Tag
Where does a protein bind (low input)?
Low
Yes
5–8 M reads
Highest
Active marks, low cell numbers
CUT&RUN
Balanced protein–DNA profiling
Low to moderate
Yes
8–15 M reads
High
TFs, histone marks, lower bias
Hi-C
How is chromatin organized in 3D?
High (live cells)
No
200 M+ read pairs
N/A
Compartments, TADs, loops
DAP-Seq
Where does a TF bind (in vitro)?
In vitro
No
20–30 M reads
High
Non-model organisms, plants
Selection Strategy:
Define your biological question first. Protein–DNA interaction mapping (ChIP-seq, CUT&Tag, or CUT&RUN), chromatin accessibility profiling (ATAC-seq), or three-dimensional conformation (Hi-C) address fundamentally different aspects of chromatin biology.
Consider sample input. CUT&Tag and ATAC-seq are preferable when cell numbers are limited. A 2025 benchmark study confirmed that CUT&Tag achieves the highest signal-to-noise ratio among chromatin-protein interaction methods, though ChIP-seq remains more effective for repressive histone marks such as H3K27me3.
For non-model organisms. DAP-seq enables transcription factor binding mapping without species-specific antibodies.
For challenging samples. Specialized protocols exist for FFPE tissues (ATAC-seq, ChIP-seq) and low-input material. Contact us to discuss feasibility.
For multi-omics integration. ATAC-seq and RNA-seq can be combined from the same sample to link chromatin accessibility with gene expression.
Workflow
End-to-End Workflow and Quality Control
Our chromatin analysis service follows a standardized workflow with quality control checkpoints at every stage.
Sample Receipt and Quality Assessment — QC Checkpoint: Sample integrity verification; viability assessment (ATAC-seq requires >80% viability); crosslinking confirmation (ChIP-seq, Hi-C); DNA quantification and fragmentation analysis.
Library Preparation — QC Checkpoint: Fragment size distribution analysis; adapter dimer assessment; library yield quantification; qPCR-based enrichment validation (ChIP-seq, CUT&Tag).
Data Quality Control — QC Checkpoint: FRiP (Fraction of Reads in Peaks) for ChIP-seq and CUT&Tag; TSS enrichment score and fragment size periodicity for ATAC-seq; contact matrix quality metrics for Hi-C.
Custom visualization — publication-ready figures tailored to your study
Pathway analysis — functional enrichment of peak-associated genes
Epigenomic data analysis — see our dedicated Epigenomic Data Analysis service for detailed options
Demo Results
Representative Data and Demo Results
Below are representative data types delivered with each chromatin analysis project. These demo results illustrate the quality and depth of our standard bioinformatics outputs, showcasing the key QC metrics, visualizations, and analytical results researchers can expect.
ChIP-seq and CUT&Tag Quality Metrics:
FRiP (Fraction of Reads in Peaks) — quantifies signal-to-noise ratio by measuring the proportion of reads falling within called peak regions.
Peak enrichment heatmap — visualizes normalized read density across called peaks, confirming strong, reproducible enrichment at target regions.
Library complexity curve — assesses whether sequencing depth is sufficient to capture the full diversity of enriched fragments.
Fragment size distribution — the characteristic nucleosome periodicity pattern (~180, 360, 540 bp) confirms successful capture of both nucleosome-free and mono/di-nucleosome fragments.
TSS enrichment score — measures read density around transcription start sites, with scores typically >8 indicating high-quality ATAC-seq libraries.
Genomic feature distribution — pie chart or bar graph showing the proportion of peaks in promoters, introns, exons, and distal intergenic regions.
Transcription factor footprinting — single-nucleotide resolution protection profiles identifying specific TF binding events in open chromatin.
Hi-C and 3D Genome Visualizations:
Contact matrix heatmap — genome-wide interaction frequency map with visible chromosome territories and TAD structures along the diagonal.
Compartment A/B eigenvector plot — identifies active (A) and inactive (B) chromatin compartments across the genome.
Virtual 4C / loop tracks — interaction frequency plots from a selected viewpoint, revealing local chromatin contacts.
Multi-Technology Comparative Analyses:
Motif enrichment analysis — identifies transcription factor binding motifs enriched within differential peak regions (ChIP-seq / ATAC-seq).
Differential peak volcano plot — statistically significant gained/lost chromatin accessibility or binding between conditions.
Peak annotation summary — genomic context of identified peaks (promoter, intron, intergenic, etc.) for downstream functional interpretation.
Integrative visualization — combined tracks showing ATAC-seq accessibility, ChIP-seq enrichment, and Hi-C interactions at key loci.
All demo results are generated from representative internal datasets and reflect the standard quality and analysis depth delivered with every project. Actual figures are customized to your specific experimental design, sample type, and research question.
Applications
Applications Across Research Areas
Cancer Epigenomics and Liquid Biopsy
Chromatin analysis methods are widely applied in cancer research to identify tumor-specific regulatory alterations. A large-scale single-cell ATAC-seq study across eight cancer types (227,063 nuclei) demonstrated that chromatin accessibility landscapes are strongly shaped by copy number alterations and can distinguish malignant from normal cells (Sundaram et al., Science, 2024). In liquid biopsy, cfChIP-seq using H3K36me3 has been shown to accurately distinguish non-small cell from small cell lung cancer from 1 mL of plasma (Maansson et al., Molecular Oncology, 2023).
Developmental and Stem Cell Biology
ATAC-seq and ChIP-seq are used to map dynamic changes in chromatin accessibility and histone modification landscapes during differentiation. The identification of transcription factors such as TFDP1 as global modulators of chromatin accessibility via CRISPR-based screening opens new avenues for understanding cell fate regulation (Ishii et al., Nature Genetics, 2024).
Plant Epigenetics and Non-Model Organisms
Hi-C and its derivatives have enabled 3D genome analysis in a wide range of plant species. A 2024 study in Nature Communications used Hi-C to discover that PDS5 proteins negatively regulate TAD-like domain formation in Arabidopsis thaliana, revealing conserved and divergent principles of genome organization across kingdoms.
Precision Medicine and Biomarker Discovery
Epigenomic profiling is increasingly integrated into precision medicine pipelines. Chromatin accessibility signatures derived from patient samples can identify active regulatory elements, nominate therapeutic targets, and classify disease subtypes. Integrating chromatin analysis with transcriptomic data provides a more complete picture of gene regulatory networks underlying disease.
Case Study
Case Study: cfChIP-seq for Non-Invasive Lung Cancer Molecular Subtyping
FAQ
Frequently Asked Questions
References
Wang et al., Frontiers in Cell and Developmental Biology (2025). Benchmark of chromatin–protein interaction methods in haploid round spermatids. https://doi.org/10.3389/fcell.2025.1572405
Maansson et al., Molecular Oncology (2023). Cell-free chromatin immunoprecipitation can determine tumor gene expression in lung cancer patients. https://doi.org/10.1002/1878-0261.13394
Sundaram et al., Science (2024). Single-cell chromatin accessibility reveals malignant regulatory programs in primary human cancers. https://doi.org/10.1126/science.adk9217
Ishii et al., Nature Genetics (2024). Genome-wide ATAC-see screening identifies TFDP1 as a modulator of global chromatin accessibility. https://doi.org/10.1038/s41588-024-01658-1
