ChIP-seq (histone & TF)
Narrow and broad peak calling for transcription-factor binding and histone modifications, with input normalization and quality metrics.
Core Bioinformatics
Epigenomics & Regulatory Analysis
From raw reads to a map of gene regulation. We run ChIP-seq, ATAC-seq, CUT&RUN, and DNA-methylation pipelines—calling peaks, differential binding and accessibility, and methylated regions, then layering motif and pathway context—and hand back tracks, tables, and figures documented for publication and review.
FASTQ · BAM in
Peaks · tracks · DMRs out
Typical turnaround 3–7 days
Individual pricing from $149
Illustrative sample output
H3K27ac
ATAC
peaks
Overview
Rigorous regulatory analysis, without the in-house pipeline overhead
Epigenomics turns sequencing reads into a map of how the genome is regulated—where proteins bind, which regions are open, and where DNA is methylated—and how that regulation shifts between conditions or cell types. The hard part is rarely running a single tool; it is choosing peak callers and statistical models suited to your assay, handling blacklist regions and input controls correctly, and documenting every decision so the result survives peer review.
We build and run that workflow for you. Whether you have a histone-mark ChIP-seq series, an ATAC-seq accessibility screen, or whole-genome bisulfite data, we take it through QC, alignment, peak or methylation calling, differential analysis, and functional annotation using established, peer-reviewed tools—never opaque in-house black boxes—and return results with the tool versions and parameters recorded for full reproducibility.
Capabilities
What we analyse
One service spanning the regulatory genome—protein–DNA binding, chromatin accessibility, 3D architecture, and DNA methylation.
ATAC-seq accessibility
Genome-wide open-chromatin mapping with Tn5-shift correction, peak calling, and differential-accessibility analysis across conditions.
CUT&RUN & CUT&Tag
Low-input, low-background profiling of binding and histone marks with sparse-signal peak callers tuned for the assay.
DNA methylation
Per-cytosine methylation from WGBS, RRBS, and EM-seq, with differentially methylated position and region calling.
Differential binding & accessibility
Replicate-aware, FDR-controlled comparison of peaks between conditions on a consensus peak set, annotated to nearby genes.
Motif & footprinting
De novo and known-motif enrichment in peaks, plus TF-footprinting from ATAC signal to infer occupancy.
Hi-C & conformation
Contact-matrix construction, TAD and loop calling, and compartment analysis to resolve 3D genome architecture.
Single-cell epigenomics
scATAC-seq and single-cell methylation: QC, dimensionality reduction, clustering, and per-cluster peak and motif analysis.
The Pipeline
How an epigenomics analysis runs
A transparent, best-practice sequence—each step chosen for your assay and documented in the final report. Nothing is a black box.
Steps are adapted to your assay: ChIP vs. ATAC vs. bisulfite, narrow vs. broad marks, with vs. without input controls. We confirm the plan with you before any compute begins.
Quality control & trimming
Raw-read QC, adapter and quality trimming, and a per-sample quality summary before anything downstream.
Tools: FastQC · MultiQC · fastp · Trim Galore
Alignment & filtering
Mapping to your reference, then duplicate removal, quality filtering, and blacklist-region exclusion for clean signal.
Tools: Bowtie2 · BWA · Picard · ENCODE blacklist
Signal & QC metrics
Normalized coverage tracks plus assay-specific quality: cross-correlation, FRiP, TSS enrichment, and fragment-size profiles.
Tools: deepTools · phantompeakqualtools · ATACseqQC
Peak / methylation calling
Narrow or broad peak calling for ChIP/ATAC/CUT&RUN, or per-cytosine methylation extraction for bisulfite data.
Tools: MACS3 · SEACR · Bismark · MethylDackel
Differential analysis
Replicate-aware, FDR-controlled differential binding, accessibility, or methylation on a consensus region set.
Tools: DiffBind · csaw · methylKit · DSS
Annotation & motifs
Peak-to-gene annotation, motif enrichment and footprinting, and pathway context to interpret regulatory changes.
Tools: ChIPseeker · HOMER · MEME · GREAT
Reporting & delivery
Signal tracks, region tables, publication-quality figures, a QC report, and reproducible methods with every tool version.
Tools: deepTools · IGV · versioned methods manifest
Tools & Technologies
Established, peer-reviewed tools—matched to your data
We select from the field's standard toolkit rather than forcing every dataset through one pipeline. A representative set of what we work with:
Read QC & preprocessing
FastQC
MultiQC
fastp
Trim Galore
Cutadapt
Alignment & filtering
Bowtie2
BWA
Picard
Samtools
deepTools
ENCODE blacklist
Peak calling
MACS3
Genrich
SEACR
epic2
phantompeakqualtools
DNA methylation
Bismark
BWA-meth
MethylDackel
methylKit
DSS
minfi
Differential analysis
DiffBind
csaw
bsseq
THOR
Motif, footprinting & annotation
MEME Suite
HOMER
JASPAR
TOBIAS
chromVAR
ChIPseeker
GREAT
Hi-C & conformation
HiC-Pro
Juicer
cooler
cooltools
TADbit
Single-cell & review
ArchR
Signac
SnapATAC2
IGV
Reference Resources
Public knowledge behind every result
Peaks and methylation calls are only as useful as the annotation around them. We build on the community's authoritative, versioned resources.
- ENCODE
- Comprehensive functional-genomics reference for regulatory elements and signal.
- Roadmap Epigenomics
- Reference epigenomes across human tissues and cell types.
- JASPAR
- Curated, open transcription-factor binding-motif models for enrichment.
- ChIP-Atlas
- Integrated public ChIP-seq, ATAC-seq, and bisulfite peak collections.
- Ensembl Regulatory Build
- Annotated promoters, enhancers, and regulatory features for context.
- ENCODE blacklist
- Problematic, high-signal regions excluded to avoid false peaks.
- GENCODE
- Gene models underpinning peak-to-gene and DMR-to-gene annotation.
- GO & Reactome
- Ontologies and pathways for enrichment of regulated gene sets.
- GEO / SRA
- Public archives for reprocessing, meta-analysis, and validation.
Choosing an Assay
ChIP-seq vs. ATAC-seq vs. bisulfite-seq
There is no single best assay—only the right one for your question and material. A quick orientation; we will help you decide.
| Dimension | ChIP-seq | ATAC-seq | Bisulfite-seq |
|---|---|---|---|
| Measures | Binding of a specific protein or histone mark | Genome-wide open (accessible) chromatin | Per-base DNA methylation |
| Needs | A validated antibody & input control | Low cell input; no antibody | Bisulfite/EM conversion; higher depth |
| Typical output | Narrow/broad peaks, signal tracks | Accessibility peaks, footprints | Methylation levels, DMPs / DMRs |
| Relative effort | Moderate; antibody-dependent | Low input, fast turnaround | Highest depth & compute |
| Best suited to | Specific TF or histone-mark questions | Regulatory landscape & discovery | Methylation state & imprinting |
What You Receive
A complete, documented deliverable
Not just a BED file dropped in a folder—every output you need to analyse, publish, and reproduce the work.
- Quality-controlled alignments (BAM), duplicate-removed and filtered
- Normalized signal tracks (bigWig) for genome browsers
- Called peaks (narrowPeak / broadPeak / BED) or methylation calls
- Differential binding / accessibility / methylation tables (TSV / XLSX)
- Motif-enrichment results & peak-to-gene annotation
- QC report with FRiP, TSS enrichment & per-sample metrics
- Publication-ready methods text with tool versions
Built for reproducibility, not just a result
Every pipeline follows documented best practices—proper input controls, blacklist handling, and replicate-aware statistics—so peaks and differential calls are earned rather than assumed. We track ENCODE-style quality metrics (FRiP, cross-correlation, TSS enrichment) so signal quality is known, not guessed. Each run records its tool versions, parameters, and reference builds.
The practical payoff: your methods section writes itself, a reviewer can re-run the analysis, and a result from today can be reproduced a year from now. We will also tell you honestly when a design or sample size won't support the conclusion you're after.
FAQ
Epigenomics & regulatory questions
What researchers and project leads most often ask before starting an epigenomics project.
ATAC-seq maps open chromatin genome-wide from low input. ChIP-seq targets a specific protein or histone mark. CUT&RUN and CUT&Tag profile the same targets with far less input and lower background. We help you match the assay to your target, input amount, and question.
Quality-controlled alignments, normalized signal tracks (bigWig), called peaks (narrowPeak/broadPeak/BED), differential binding or accessibility tables, motif-enrichment results, and peak-to-gene annotation — plus publication-ready figures and methods.
Yes. We process whole-genome and reduced-representation bisulfite sequencing (WGBS/RRBS) and EM-seq, call per-cytosine methylation, and identify differentially methylated positions and regions (DMPs/DMRs). We also handle Illumina EPIC methylation arrays.
Yes. We run replicate-aware differential analysis of binding and accessibility with consensus peak sets and FDR control, then annotate the changing regions to nearby genes and enriched motifs and pathways.
We start from raw reads (FASTQ) or aligned data (BAM). If you only have sequencing files from your core facility and a reference genome, that is enough to begin. We return signal tracks, peak and region files, and annotated tables.
Yes. Linking accessibility, histone marks, or methylation to expression is often where the biology emerges — we integrate peaks and DMRs with differential-expression results to connect regulatory changes to their transcriptional consequences.
Related
Where epigenomics work often leads next
Have sequencing data ready to analyse?
Tell us your organism, data type, and question—we'll scope it honestly, including if a different design would serve you better.