1. Gene-wise variant burden and genomic characterization of nearly every gene
- Author
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Heewon Seo, Brian Y. Ryu, Ju Han Kim, and Yoomi Park
- Subjects
0301 basic medicine ,Pharmacology ,Disease gene ,Prioritization ,In silico ,Complex disease ,Genetic Variation ,Computational biology ,Genomics ,Biology ,Mendelian Randomization Analysis ,Mendelian disease ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Pharmacogenetics ,Mutation ,Genetics ,Molecular Medicine ,Humans ,Gene ,030217 neurology & neurosurgery ,Gene prioritization - 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.
- Published
- 2020