Driving Accurate Variant Classification with Scientific Rigor

Our proprietary variant classification scheme is grounded in ACMG guidelines and shaped by Ambry’s innovation, expertise and progressive implementation.

Variant Classification at Its Best

Ambry combines proprietary analysis tools with multidisciplinary expertise, using all available evidence to classify variants and reduce uncertain results.

Proprietary Bioinformatics

Proprietary Bioinformatics

Our proprietary in-house bioinformatics and reporting tools are a cornerstone of our commitment to precision genetic diagnostics. These powerful platforms seamlessly integrate with Ambry's extensive genetics and phenotype knowledge database, ensuring every analysis we conduct is informed by a vast repository of genetic insights.

We continuously update our systems with the most clinically relevant information from scientific publications, cutting-edge research, and global genetic databases. These practices ensure every report we generate reflects the most current advancements in the field.

Interdisciplinary Team

Ambry’s collaborative and cross-functional team of experts is comprised of MD and PhD laboratory directors, biostatisticians, bioinformaticians, structural biologists, variant scientists, research scientists and genetic counselors.

Our dedicated Genomic Sciences development team continuously evaluates the latest scientific advancements in the field and regularly updates the Ambry Classifi™ program to include improvements in analytical methods and interpretation that are actively shared with the scientific community through ClinGen Expert Panel participation.

Interdisciplinary Team
Specialized Expertise

Specialized Expertise

Our team boasts unparalleled knowledge in critical genetic subspecialties, including nonsense-mediated decay, protein modeling, RNA analysis, and splicing. We also have specialized internal expert panels by therapeutic area for oncology, cardiology, and neurology. These groups are committed to utilizing gene-disease specific guidelines and criteria with a deep expertise in variant classification.

Our comprehensive understanding of the complexities of genetics allows us to provide a level of insight and precision unmatched in the field. By leveraging our unique expertise, we're able to offer comprehensive genetic analysis and interpretations that go beyond the surface, enabling precise diagnoses and personalized care plans.

Download the Variant Schemes

The Ambry Genetics Variant Classification Schemes use a points-based framework that allows for a clear understanding of a variant's classification. Ambry is dedicated to routinely updating our variant classification scheme to reflect published recommendations and scientific data to drive accurate variant interpretation and deliver high-confidence classifications.


Proactive Variant Reclassification in Hereditary Cancer Genes

Clinical Validity Scoring at Ambry Genetics

Keeping score of mutations to link genes to disease


Recommended Publications for Further Information

  1. Pejaver V et al. Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria. Am J Hum Genet. 2022 Dec 1;109(12):2163-2177.
  2. Tavtigian SV et al. Fitting a naturally scaled point system to the ACMG/AMP variant 1( guidelines. Hum Mutat. 2020 Oct;41(10):1734-1737.
  3. Bean LJH, et al. Diagnostic gene sequencing panels: from design to report—a technical standard of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2020 Feb;22(2):453-461.
  4. Tavtigian SV et al. Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genet Med. 2018 Sep;20(9):1054-1060.
  5. O'Daniel JM, et al. A survey of current practices for genomic sequencing test interpretation and reporting processes in US laboratories. Genet Med. 2017 May;19(5):575-582.
  6. Pesaran T, et al. Beyond DNA: An Integrated and Functional Approach for Classifying Germline Variants in Breast Cancer Genes. Int J Breast Cancer. 2016, 2469523.
  7. Richards S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015 May;17(5):405-24.
  8. MacArthur DG, et al. Guidelines for investigating causality of sequence variants in human disease. Nature. 2014 Apr 24;508(7497):469-76.
  9. Biesecker LG, Green RC. Diagnostic clinical genome and exome sequencing. N Engl J Med. 2014 Jun 19;370(25):2418-25.
  10. Rehm HL, et al. ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013 15(9):733-747.
  11. Thompson BA, et al. A multifactorial likelihood model for MMR gene variant classification incorporating probabilities based on sequence bioinformatics and tumor characteristics: a report from the Colon Cancer Family Registry. Hum Mutat. 2013 Jan;34(1):200-9.
  12. Green RC, et al. ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med. 2013 Jul;15(7):565-74.
  13. Caleshu C, et al. Use and interpretation of genetic tests in cardiovascular genetics. Heart. 2010 Oct;96(20):1669-75.

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