Document Type
Conference Paper/Presentation
Conference
Presented at the American Medical Informatics Association's (AMIA 2021) Annual Symposium
Publication Date
11-2021
Advisor(s)
Sabah Kadri, PhD; Director of Computational Genomics, AbbVie
Kai Lee Yap, PhD FACMG; Director of Molecular Diagnostics, Ann & Robert H. Lurie Children’s Hospital of Chicago, Assistant Professor of Pathology, Northwestern University
Disciplines
Biology
Abstract
As the scientific community continues to discover novel genetic variants associated with human constitutional disorders, there is a growing need for a standardized approach for reporting of genetic variants, as accurate variant identification is crucial for effective diagnosis and treatment. Robust identification and annotation of genetic variants relevant for human germline disorders is foundational for clinical Next Generation Sequencing (NGS) assays. Using a manually curated set of 296 variants, generated by targeted gene panel sequencing using the ~4700 gene medical exome panel on 105 patients, we evaluated the performance of two variant annotation tools (Variant Effect Predictor and Alamut Batch) for implementation in our clinical bioinformatics pipeline at the Molecular Diagnostics Laboratory at Lurie Children’s Hospital. With respect to HGVS nomenclature standards and clinical integrity, VEP produces more accurate variant annotations due to usage of updated gene transcript versions within the algorithm.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Tuteja, S.
(2021).
The Enigma of Clinical Next Generation Sequencing (NGS) based Genetic Testing Variant Annotation Tools: A Performance Evaluation Study.
Retrieved from: https://digitalcommons.imsa.edu/student_pr/97
Comments
Recipient of the Distinguished Poster Award