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PAS-GDC: Annotated ACMG gene-disease database and interactive search application for translational research in genomics and precision medicine.

Nov 07, 2022 Ahmed Lab

Ms. Habiba Abdelhalim presenting, “PAS-GDC: Annotated ACMG gene-disease database and interactive search application for translational research in genomics and precision medicine“, at the 14th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics with DREAM Challenges. 7-11 November, 2022.

Presentation Overview:

Title: PAS-GDC: Annotated ACMG gene-disease database and interactive search application for translational research in genomics and precision medicine.

Authors:

  • Raghunandan Wable, Rutgers, The State University of New Jersey., United States
  • Anirudh Pappu, Rutgers, The State University of New Jersey., United States
  • Achuth Nair, Rutgers, The State University of New Jersey., United States
  • Khushbu Patel, Rutgers, The State University of New Jersey., United States
  • Dinesh Mendhe, Rutgers, The State University of New Jersey., United States
  • Shreyas Bolla, Rutgers, The State University of New Jersey., United States
  • Sahil Mittal, Rutgers, The State University of New Jersey., United States
  • Habiba Abdelhalim, Rutgers, The State University of New Jersey., United States
  • Zeeshan Ahmed, Rutgers, The State University of New Jersey., United States

Abstract:

To efficiently practice precision medicine in the clinical settings, it is important to integrate genomic profiles of the patients with their electronic health records (EHR). The disease definition in basic sciences and genomics is simplified. However, in the clinical world diseases are classified, identified, and adopted with their International Classification of Diseases (ICD) codes, maintained by the World Health Organization (WHO). This is the era of big data, where human-related biological databases continue to grow not only in count but also in volume, posing unprecedented challenges in data curation, storage, processing, analysis, and dissemination. Regardless of limitations, these databases are helpful in interpreting the disease taxonomy, etiology, and pathogenesis. However, there is still no such comprehensive database exists, which can link clinical codes (e.g., ICD) with genomic data (e.g., genes, variants, etc.). In this project, we are focused to support translational research in genomic and precision medicine with the development of an annotated gene-disease-code database accessible through a cross-platform, user friendly, and interactive search application i.e., PROMIS-APP-SUITE: Gene Disease Codes (PAS-GDC). However, our scope is limited to the list of genes approved by the American College of Medical Genetics and Genomics (ACMG). The ACMG is an organization that vests its interests in the medical genetics field and responsible for a guideline development that is internationally accepted for gene-variant interpretation. Our application support users in searching and integrating genes, diseases, and clinical codes. It allows users to export results in text formats to facilitate sharing and importing for translational research.

Poster: