Helping families understand their risks for inherited diseases
Clinically Relevant.
Whole Genome.
We provide a more complete picture of disease risk through clinical-grade whole genome sequencing (up to 30x) and analysis–10x more information than other tests–including rare and common variants and structural alterations
Test Once.
Analyze Often.
We deliver a lifetime (birth to family planning to late life) of on-demand health insights from a single sample that continuously updates for cardiac, diabetes, autoimmune, cancer risk, and other conditions, response to certain medications, and single gene and polygenic analysis to assess risk of multifactorial diseases
Dynamic Technology.
Actionable Findings.
We generate actionable integrated disease risk scores that evolve with a patient’s lifestyle by combining multiple genes and clinical factors enhanced with the newest ML/AI technologies and analysis methods
To Lower Risk, Uncover At-Risk
Know who is at high risk for common and rare diseases and who to manage for earlier health intervention and disease management
Our Reports
Assess Risk.
Prevent Disease.
MyOme Integrated
Disease Risk
Estimate the lifetime risk of cardiac disease using genetic markers, clinical history, and lifestyle factors.
Screen Effectively.
Intervene Earlier.
MyOme Gene Panels
Assess Risk.
Prevent Disease.
MyOme Therapeutic Insights
One Sample. Insights for Life.
Gain new insights over a patient’s lifetime. MyOme analyzes data and provides reports on-demand to answer clinically relevant questions throughout a patient’s life related to risk for common and rare diseases and pharmacogenomics.
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Our Solutions
Advisors
Stephen Montgomery, Ph.D.
Associate Professor Of Pathology And Genetics
Stanford University
Trevor Hastie, Ph.D.
Professor Of Statistics And Biomedical Data Sciences
Stanford University
Russ B. Altman, M.D., Ph.D.
Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and Computer Science
Stanford University
Jacob Kitzman, Ph.D
Assistant Professor of Human Genetics Assistant Professor of Computational Medicine and Bioinformatics University of Michigan
Investors
