Scalable bioinformatic technology for diagnostic services, drug development, population genomics & more

Omics Edge’s patent-pending bioinformatic technology can process and analyze genomic and phenotypic data at an unprecedented scale providing unmatched utility for any organization performing diagnostic and drug development processes or research.

Cutting-edge Genomic Services

Omics Edge has developed proprietary and soon-to-be patent-protected bioinformatic technology that allows us to process and analyze genomic and phenotypic data at an unprecedented scale. Our bioinformatics tools can be used throughout the diagnostic and drug development process from initial discovery to post-market surveillance.


We are able to incorporate past studies, public biobank data, and private data in order to drive discovery and development. In total, we have access to about 2 million samples with phenotypic data.

Local Ancestry Prediction

Omics Edge has developed a proprietary ancestral deconvolution tool that outperforms other leading ancestry methods in both non-admixed and admixed samples. It has ~15% better overall recall and ~14% better overall precision than the next-best model.

Use cases include:
  • Facilitating fine-mapping to discover functional genetic variants driving disease progression that make ideal drug targets
  • Improving GWAS discovery by controlling for genetic confounding
  • Refining GWAS-eQTL colocalization to identify the disease mechanism
  • Improving portability of PRS for non-European populations and for admixed individuals
  • Animal and plant breeding
  • Discovering gene-ancestry and gene-environment interactions

Genomic Compression

Our proprietary genomic compression algorithm can achieve a better than 100:1 compression ratio on genomic data and is uniquely designed and developed for large biobank scale data.

Use cases include:
  • Ability to compress other biological data beyond genomic data, including multi-omic data, biometric data, and EMR
  • Lossless, designed for static storage solutions to save the maximum amount of storage space/cost
  • Ability to analyze specific parts of the data without decompressing all of it since the method compresses data in blocks the size of which can be optimized
  • AES-256 encryption to meet any current data security requirements in highly regulated environments
  • And more!

Cost Reduction

Our proprietary and soon-to-be patented compression algorithm can compress massive amounts of genetic and phenotypic data at an unprecedented scale while allowing analysis and processing to occur without the need to decompress the entire dataset.

Genetic Imputation

Our proprietary imputation algorithm outperforms leading imputation methods across all allele frequencies, performing exceedingly well for rare variants, where all other models struggle.

Use cases include:
  • Boosting power in GWAS discovery
  • Ability to test for rarer variants that carry larger effect sizes
  • Better signal resolution to fine-map causal variants and select candidate variants for downstream functional analysis
  • Increased accuracy of PRS by integrating rare variants

Companion Diagnostics Pipeline

As a proof of concept, we built a genomic companion diagnostic pipeline based on matching people's genetic data to lifestyle, diet, and vitamin and mineral recommendations. In the graph, you can see the users’ biomarker data before and after using the platform, which indicate improvements in fasting glucose levels (mg/dL) (a) and in HbA1c levels.

Polygenic Risk Scores

Polygenic Risk Scoring (PRS) allows us to know the genetic predispositions for a myriad of common health conditions including the top causes of death and health care expenses such as cardiovascular disease or diabetes. Our proprietary PRS algorithm has consistently outperformed other leading models.

Relationship Inference

We provide a variety of relationship inference services using genetic data including

  • Cryptic relative detection
  • Pedigree reconstruction
  • Paternity testing

Advanced Diagnostic Services

Polygenic risk scores for complex diseases

By utilizing our cutting-edge imputation models that outperform today’s industry-leading algorithms, we can provide highly accurate ancestry-informed polygenic risk scores for hundreds of complex diseases.

Absolute risk predictions for complex diseases

With the inclusion of an individual’s lab results, demographics, ethnic background, family history and other key descriptors, we can expand relative risk models into predictions of individual disease risk which incorporate both genetic and environmental factors.

Companion Diagnostic (CDx) services

Based on an individual’s genetic data, our cutting-edge technology can select drugs, therapies and lifestyle interventions that are likely be most effective and predict which ones may lead to adverse effects.

Identification of genetic disorders, traits and carrier status

We can provide direct genotyping services to identify diseases linked to specific genetic variants and identify individuals’ carrier status for various genetic disorders.

Revolutionary Drug Development

Drug Discovery

With 2 million+ samples of genetic data and a comprehensive library of past studies, we can help guide the choice of therapeutic targets in drug development, and identify potentially problematic pathways which have multi-disease roles.

Services include:
  • Case-control design / binary traits GWAS
  • Continuous traits GWAS and PheWAS
  • Multi-trait GWAS and PheWAs
  • Identification of potential drug targets based on functional genomic variants implicated in disease
  • Identification of ideal drug targets by determining which biochemical pathways are disturbed by genetic variants driving the disease

Clinical trials and

Perform clinical trials more efficiently and reduce trial-and-error with our technology that can provide accurate predictions and recommendations based on an individual’s genetic data.

Services include:
  • Identifying and predicting individual drug responses
  • Controlling for genetic confounding variables in clinical trials
  • Identifying individuals more likely to have adverse events
  • Matching medications and dosages with individuals based on their genetics
  • Identifying variants known to impact drug response (Pharmacogenomics)

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