Gene-wise variant burden and genomic characterization of nearly every gene

Author:

Park Yoomi1,Seo Heewon12,Y Ryu Brian1,Kim Ju Han13

Affiliation:

1. Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, 03080, Korea

2. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, M5G 2M9, Canada

3. Center for Precision Medicine, Seoul National University Hospital, Seoul, 03080, Korea

Abstract

Aim: Current gene-level prioritization methods aim to provide information for further prioritization of ‘disease-causing’ mutations. Since, they are inherently biased toward disease genes, methods specific to pharmacogenetic (PGx) genes are required. Methods: We proposed a gene-wise variant burden (GVB) method that integrates in silico deleteriousness scores of the multitude of variants of a given gene at a personal-genome level. Results: GVB in its simplest form outperformed the two state-of-the-art methods with regard to predicting pharmacogenes and complex disease genes but not for rare Mendelian disease genes. GVB* adjusted by paralog counts robustly performed well in most of the pharmacogenetic subcategories. Seven molecular genetic features well characterized the unique genomic properties of PGx, complex, and Mendelian disease genes. Conclusion: Altogether, GVB is an individual-specific genescore, especially advantageous for PGx studies.

Publisher

Future Medicine Ltd

Subject

Pharmacology,Genetics,Molecular Medicine

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