Our epigenetic testing services provide quick and cost effective processing of your samples that will move your research forward.
DNA methylation is a primary factor in regulating gene expression. We provide end-to-end, cost-effective DNA methylation testing and analysis in a high throughput, CLIA-certified laboratory for mice and humans.
We have proprietary intellectual property that covers a wide swath of technology in the use of epigenetic signatures associated with longevity risk classification, probe selection, and supervised machine learning.
Our Human Methylation Array enables researchers to seamlessly process human samples and examine thousands of CpGs using state-of-the-art bioinformatics.
Features & Benefits:
- Based on Illumina’s Infinium MethylationEPIC BeadChip plus content from the Infinium Human Methylation 450K BeadChip.
- Detects DNA methylation levels at over 860,000 CpGs.
- Includes comprehensive lab processing and bioinformatic pre- and post-processing.
- End-to-end solution yields analysis-read data to aid researchers in publishing results quickly.
Our newly designed, first-of-its-kind, Mouse Methylation array was developed in collaboration with Van Andel Institute and Illumina, and was created to support biological research efforts in precision-based diagnostics, therapeutic medicine, and longevity.
- Usable in all inbred and outbred strains of Mus musculus, including subspecies.
- ~265,000 CpGs in enhancer regions, gene bodies, promoters, and CpG islands.
- CpGs whose methylation was found predictive of epigenetic age.
- DNA methylation probes were designed for CpGs conserved among more than 15 common mouse strains.
- End-to-end solution produces analysis-ready data to reduce time between analysis and publishing.
- CpGs in common PMD and in solo-WCGW context
- CpGs with putative mono-allelic methylation (adult and placenta tissues)
- CpGs within 500bp of flanking miRNAs
- CpGs specifically methylated or unmethylated in germ cell development
- CpGs specifically methylated or unmethylated in zygotes and mouse placenta
- CpGs located at or close to CTCF binding sites
- CpGs in imprinting-associated differentially methylated regions
- CpGs located in the mouse mitochondrial genome 42
- Randomly-selected CpGs (autosomes and sex-chromosomes)
- Probes targeting CpGs in multi-copy transposable elements
- Probes to target non-CpG cytosine methylation
- Strain-distinguishing SNPs based on 10 common inbred strains
- Control probes to assess proper probe hybridization and extension
Our research is focused on the discovery and commercialization of epigenetic signatures that cover human health, wellness, and aging.
How to Place an Order
If you are already a FOXO™ customer, contact your sales representative directly to place an order. If you’re new here, request a quote or contact us at: 612.562.9447.
Open Source Bioinformatics Software
We believe in sharing tools and resources that support the research community and lead to groundbreaking discoveries. Our open source bioinformatic software packages are simplifying and automating the labor-intensive preprocessing, quality control, and analyses commonly involved in the analysis of complex DNA methylation data.
- Automates analysis of epigenetic data from Illumina arrays that measure DNA modifications that are altered in response to human behavior and biological processes
- Written in Python, these open source software packages can run natively in command line, Jupyter notebooks, or automation scripts
- Improves user experience for researchers by automating previously laborious steps in epigenetic data pre-processing and quality control
Methylprep is part of a methyl-suite of Python packages that provide functions to process and analyze DNA methylation data from Illumina arrays (27, 450k & EPIC/850k supported) and download/process public data sets from GEO or ArrayExpress
Methylcheck works in conjunction with Methylprep and contains high-level APIs for filtering processed data from local files that have been downloaded from the NIH GEO database or processed as a set of idat files.
Run linear or logistic regression on all probes to identify points of interest in the methylome where DNA is differentially modified. These regression results can then be used to create volcano plots and manhattan plots.