Epigenetics
DNA Methylation
Mapping & Methylation calling
We offer comprehensive DNA methylation analysis using Whole Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), and enzymatic methylation methods. Our workflows include high-quality read alignment, methylation calling, and quality control to ensure accurate and reproducible epigenetic profiles across the genome.
Differential methylation
Our team performs robust differential methylation analysis to identify genomic regions with significant methylation changes between conditions. Our workflows support discovery of epigenetic biomarkers and regulatory elements linked to disease, development, or environmental response.
Biological clock
Our Bioinformaticians provide accurate estimation of biological age using DNA methylation-based clocks. By comparing epigenetic and chronological age, we assess age acceleration and its association with health, disease, and environmental exposures. Our workflows ensure reliable predictions across a range of tissues and study designs.
Direct methylation detection from Nanopore reads
We offer direct DNA methylation detection from Oxford Nanopore sequencing reads without the need for chemical conversion. Our workflows leverage raw signal-level data to accurately identify methylation patterns across the genome, enabling real-time, long-read epigenetic analysis for complex regions and structural variants.
Chromatin Accessibility & TF Binding
Gene expression regulation: ATAC-seq, ChIP-seq, CUT&TAG
We provide expert support for chromatin profiling using ATAC-seq, ChIP-seq, and CUT&TAG technologies. Our workflows ensure high-quality preprocessing, including quality control, adapter trimming, and accurate alignment to reference genomes, laying the groundwork for reliable insights into chromatin accessibility and protein-DNA interactions.
Peak calling
Our experts perform precise peak calling on chromatin profiling data (ATAC-seq, ChIP-seq, CUT&TAG) to identify regions of significant enrichment. Our optimized workflows enhance detection of regulatory elements, transcription factor binding sites, and histone modification peaks for downstream functional analysis.
Motif analysis
We offer comprehensive motif analysis to detect and characterize DNA sequence patterns within regulatory regions identified from chromatin profiling data. By uncovering potential transcription factor binding sites, our analysis helps elucidate the regulatory networks that control gene expression and cellular function.
RNA-DNA interaction analysis: ChiRP-seq, RAP-seq
We analyze RNA-DNA interaction data generated from ChIRP-seq and RAP-seq experiments to accurately identify and map genomic regions associated with specific RNAs. This detailed mapping provides valuable insights into how RNA molecules influence chromatin organization, gene regulation, and epigenetic mechanisms. By integrating these data with other omics layers, we help uncover complex regulatory networks and functional roles of non-coding RNAs in various biological processes and diseases.
3D Genomics
Hi-C / Capture Hi-C
Our team offers analysis of Hi-C and Capture Hi-C data to explore the 3D organization of the genome. By mapping chromatin interactions at varying resolutions, these techniques reveal spatial genome architecture and regulatory contacts critical for gene expression and cellular function.
Chromatin loop & TAD analysis
We provide analysis of chromatin loops and Topologically Associating Domains (TADs) from 3D genome data. Identifying these structural features helps reveal genome organization principles and their role in regulating gene expression and genome stability.
Visualization
We offer detailed visualization of Hi-C data, presenting chromatin interactions, loops, and 3D genome structure in an intuitive and accessible way. This visualization supports clearer understanding of spatial genome organization and its functional implications.
Single-cell Epigenomics
scATAC-seq, scMethyl-seq
Our team support analysis of single-cell epigenomic data including scATAC-seq and scMethyl-seq. These techniques enable profiling of chromatin accessibility and DNA methylation at single-cell resolution, revealing cellular heterogeneity and epigenetic regulation within complex tissues.
Epigenetic trajectory inference
We use computational approaches to reconstruct epigenetic trajectories from single-cell data. This enables tracking dynamic changes in chromatin accessibility or DNA methylation, uncovering cellular differentiation paths and regulatory programs at single-cell resolution.
Joint analysis with single-cell RNA-seq
We integrate single-cell epigenomic data with single-cell RNA-seq to provide a comprehensive view of cellular states and regulatory mechanisms. This joint analysis links gene expression profiles with chromatin accessibility or methylation, enabling deeper insights into cell identity and function.