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Babb, Lawrence

https://orcid.org/0000-0002-2455-2227

Mayo Clinic

Broad Institute

Citations 5

The GA4GH Categorical Variation Representation Specification: A Unified Computational Framework for Reasoning over Genomic Variant Categories
Puthawala, Daniel , Reardon, Brendan , Babb, Lawrence , Kuzma, Kori , Stevenson, James , Goar, Wesley , Dolin, Robert H , Freimuth, Robert R. , Procknow, Catherine, Pitel, Beth A. , Kundu, Parijat , Rampersad, Akash , Allen, Eliezer M Van, Babb, Lawrence , Kuzma, Kori , Stevenson, James S , Goar, Wesley A , Pitel, Beth A , Van Allen, Eliezer M , Wagner, Alex H , Freimuth, Robert R , Wagner, Alex H.

No container title available | February 12, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.02.10.705161 Get It

Abstract Categorical variants, or sets of genomic alterations constrained by shared properties, are pervasive across clinical, regulatory, and research domains in the biomedical ecosystem, yet their inconsistent and non-computable representation hinders data interoperability and clinical interpretation. We surveyed genomic knowledgebases spanning regulatory approvals and the biomedical literature and found that categorical variants underpin a substantial proportion of clinical genomics knowledge, but are largely described using incompatible bespoke models. To address this, we developed the GA4GH Categorical Variation Representation Specification (Cat-VRS), a constraint-based framework that provides a unified computable representation for both precise and intentionally broad categories across molecular and systemic variant domains. Cat-VRS enables harmonization of genomic knowledgebases, computable category-based search, and automated matching between assayed variants and categorical entities in clinical and research contexts. By providing a principled, extensible model for categorical variation, Cat-VRS enables computable reasoning over genomic variant categories and establishes a foundation for the standardized representation and exchange of genomic knowledge.
Development and application of a computable genotype model in the GA4GH Variation Representation Specification
Goar, Wesley , Babb, Lawrence , Cline, Melissa , Kuzma, Kori , Lee, Jennifer , Nelson, Tristan , Smith, Anastasia , Stahl, Kathryn , Bratulin, Anastasia L. , Babb, Lawrence , Chamala, Srikar , Freimuth, Robert R. , Hart, Reece K. , Prlić, Andreas , Riehle, Kevin P. , Yates, Andrew , Rehm, Heidi L. , Wagner, Alex H.

Biocomputing 2023 | November 24, 2022 | Volume: No volume available | Issue: No issue available | Pages: 383-394

10.1142/9789811270611_0035 Get It

Abstract 1177: Introduction of the GA4GH Variation Representation Specification (VRS) and supporting tools for discovery and exchange of clinical genomic and cytogenomic knowledge in cancers
Kuzma, Kori , Stevenson, James , O'Sullivan, Colin, Chaudhari, Bimal P. , Brush, Matthew , Nelson, Tristan , Cline, Melissa , Walsh, Brian , Cannon, Matthew V. , Liu, Jiachen , Freimuth, Robert R. , Baudis, Michael , Griffith, Obi L. , Griffith, Malachi , Babb, Lawrence , Liu, Xuelu, Wagner, Alex H.

Cancer Research | June 15, 2022 | Volume: 82 | Issue: 12_Supplement | Pages: 1177-1177

10.1158/1538-7445.am2022-1177 Get It

Abstract Precision oncology is the practice of interpreting the clinical significance of observed molecular changes in patient neoplasms, potentially impacting medical decision making and care. This process is labor-intensive and (among other challenges) involves accurately translating between variation representation conventions from one resource to the next. For example, differences in representations of Copy Number Variation (CNV) from genomic regions, cytogenomic bands, or gene features create challenges in knowledge matching due to lack of standards covering all of these modalities of observed variation.The Global Alliance for Genomics and Health (GA4GH; ga4gh.org) is an international collaborative of genomic data sharing initiatives (Driver Projects) developing genomic data sharing standards within a human rights framework. GA4GH recently published the Variation Representation Specification (VRS; pronounced “verse”), a standard for the computational representation of biomolecular variation. VRS is a terminology, schema, and associated conventions for creating uniquely identifiable and federatable representations of molecular variation. VRS has formal data classes well-suited to differentiating between variation on a single molecule (e.g. tandem duplications) from variation measured at a systemic level (e.g. genome-wide copy number variation). In addition to molecular sequence variation, VRS also supports variation on cytogenetic coordinate systems and genes, making it well-suited to representing variation associated with cancer biomarkers.We demonstrate the use of VRS to model reported gene-associated CNVs from the AACR Project GENIE cohort, to aid in the computational discovery of evidence from clinico-genomic knowledgebases with genomic or cytogenomic CNV representations. We highlight the use case of knowledge matching to the Atlas of Genetics and Cytogenetics in Oncology and Haematology (“the Atlas”; atlasgeneticsoncology.org), a cytogenetics resource historically driven by user website navigation. Using VRS search tools we developed for the Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) GA4GH Driver Project, we found that 64% of GENIE samples with reported CNVs matched clinically relevant knowledge in the Atlas. This work was enabled by programmatic search tools leveraging standard VRS object structures, demonstrating how VRS enables collection of real-world evidence across more resources without manual interpretation or custom normalization methods. We conclude with a survey of open-source tools supporting this analysis as well as search of other clinico-genomic knowledgebases with VRS, including CIViC (civicdb.org), BRCA Exchange (brcaexchange.org), and the Molecular Oncology Almanac (moalmanac.org). Citation Format: Matthew Cannon, Kori Kuzma, James Stevenson, Jiachen Liu, Colin O'Sullivan, Bimal P. Chaudhari, Matthew Brush, Robert R. Freimuth, Tristan Nelson, Michael Baudis, Obi L. Griffith, Malachi Griffith, Lawrence Babb, Melissa S. Cline, Xuelu Liu, Brian Walsh, Alex H. Wagner. Introduction of the GA4GH Variation Representation Specification (VRS) and supporting tools for discovery and exchange of clinical genomic and cytogenomic knowledge in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1177.
Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example
Aronson, Samuel , Babb, Lawrence , Ames, Darren C., Gibbs, Richard A. , Connelly, John, Marsolo, Keith , Hartzler, Andrea L. , Liang, Wayne H. , Ralston, James D. , Devine, Emily Beth , Murphy, Shawn N. , Freimuth, Robert R. , Rasmussen, Luke V. , Peterson, Josh F. , Robinson, Jamie R. , Wiley, Ken, Taylor, Casey Overby , Group, eMERGE Network EHRI Working, Caraballo, Pedro J. , Babb, Lawrence , Rasmussen, Luke V , Freimuth, Robert R , Venner, Eric , Weng, Chunhua , Williams, Marc S , Chute, Christopher G. , Kullo, Iftikhar J. , Wehbe, Firas , Group, eMERGE Network EHRI Working, Peterson, Josh F

Journal of the American Medical Informatics Association | April 19, 2018 | Volume: 25 | Issue: 10 | Pages: 1375-1381

10.1093/jamia/ocy051 Get It

AbstractThe eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.