A methodological framework for accommodating Cancer Genomics Information in OMOP-CDM using Variation Representation Specification (VRS)

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Authors: Elisa Benetti, Guido Scicolone, Muhammad Tajwar, Corrado Masciullo, Gabriele Bucci, Michela Riba
Cited by: 0
References: 7

Abstract

ABSTRACT The OMOP Common Data Model (OMOP CDM) in which observational health data are organized and stored is a broadly accepted data standard which helps clinical research facilitating federation study protocols. In case of cancer studies, there is a growing need to incorporate cancer genomics data in a standardized way. Starting from a brief overview of the basic features of the OMOP CDM, we imagine a path of increasing complexity for including known biomarker genomic data coming from pathology or reports or clinical laboratory findings, towards storing thousands of known and unknown variants coming from genome sequencing data. Data should be stored using standardized identifiers, including those defined by the Global Alliance for Genomics and Health (GA4GH). We propose a scalable strategy for storing genomics variants in increasingly complex scenarios and present KOIOS-VRS, a pipeline that automates the conversion of VCF files into OMOP compatible format.

Fields of Study & Subjects

Cancer Genomics and Diagnostics Electronic Health Records Systems Biomedical Text Mining and Ontologies

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
10 February 2026
Language
EN
Document type
Preprint