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Comprehensive bioinformatic analysis with publication-ready figures
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Spike-In control ensures data quality in every single sample
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Compatible with low input and any species with a reference genome
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Service Options

Quantitative analysis from preliminary screening to complete genome

Reduced Representation Bisulfite Sequencing (Classic RRBS)
Efficient genome-wide analysis to detect nearly all CpG islands and gene promoter. 1.5-2 million sites at 5-10X average minimum coverage*.

Methyl-MiniSeq®
Robust biomarker discovery to detect twice as many unique CpG sites compared to Classic RRBS. 3-4 million unique CpG sites at 5-10X average minimum coverage.*

Whole Genome Bisulfite Sequencing (Methyl-MaxiSeq®)
DNA methylation information on entire methylome, including less common CHG and CHH contexts.

*Coverage estimates based on the human genome.

User-Friendly & Comprehensive Report

Publication-Ready Methylation Profiling Analysis at Your Hands

Methyl-MiniSeq Service Report overview

Full Analysis Includes:

  • Differentially methylation sites (DMS)
  • Differentially methylation regions (DMR)
  • Gene annotation
  • Heatmap clustering
  • Methylation value violin plots on global scale

In situ Spike-in Control in Every Sample

High quality data is ensured even in non-traditional organisms

Methylation Ratio Correlation

In situ Spike-in control sample

The observed methylation levels of a spike-in control composed of 6 unique double-stranded synthetic amplicons that have specific DNA methylation levels ranging from 0 to 100% is highly correlated with expected methylation level using conventional WGBS. Analysis of spike-in control using our bioinformatic service ensures high quality data is produced in every single sample.

Bisulfite Conversion Efficiency

Species Non-CpG context Spike-in control
Cotton 81% 99%
Soybean 89% 99%
Arabidopsis thaliana 97% 99%
Human 99% 99%
Cattle 99% 99%

Bisulfite conversion efficiency from various species calculated using both non-CpG context from gDNA and in situ spike-in control shows that the spike-in control is a better measurement for bisulfite conversion efficiency when working with non-traditional organisms that have methylation in non-CpG context

Robust Methylation Profiling With Low Input

CpG Sites Overlap
CpG Sites Overlap Diagram
Methylation Ratio Conversion
Metylation Ratio Conversion Plot Graph

RRBS libraries prepared using 10 ng and 100 ng human liver genomic DNA indicate the majority of CpG sites analyzed in low input overlap with high input (left), and the methylation ratio is highly correlated between the two input amounts (right).

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