Development and Application of a Computable Genotype Model in the GA4GH Variation Representation Specification

Overview

Journal Pac Symp Biocomput

Publisher World Scientific

Specialty Biology

Date 2022 Dec 21

PMID 36540993

Authors

Wesley Goar

Lawrence Babb

Srikar Chamala

Melissa Cline

Robert R Freimuth

Reece K Hart

Kori Kuzma

Jennifer Lee

Tristan Nelson

Andreas Prlic

Kevin Riehle

Anastasia Smith

Kathryn Stahl

Andrew D Yates

Heidi L Rehm

Alex H Wagner

Affiliations

Soon will be listed here.

Abstract

As the diversity of genomic variation data increases with our growing understanding of the role of variation in health and disease, it is critical to develop standards for precise inter-system exchange of these data for research and clinical applications. The Global Alliance for Genomics and Health (GA4GH) Variation Representation Specification (VRS) meets this need through a technical terminology and information model for disambiguating and concisely representing variation concepts. Here we discuss the recent Genotype model in VRS, which may be used to represent the allelic composition of a genetic locus. We demonstrate the use of the Genotype model and the constituent Haplotype model for the precise and interoperable representation of pharmacogenomic diplotypes, HGVS variants, and VCF records using VRS and discuss how this can be leveraged to enable interoperable exchange and search operations between assayed variation and genomic knowledgebases.

Citing Articles

HGVS Nomenclature 2024: improvements to community engagement, usability, and computability.

Hart R, Fokkema I, DiStefano M, Hastings R, Laros J, Taylor R Genome Med. 2024; 16(1):149.

PMID: 39702242 PMC: 11660784. DOI: 10.1186/s13073-024-01421-5.

A corpus of GA4GH phenopackets: Case-level phenotyping for genomic diagnostics and discovery.

Danis D, Bamshad M, Bridges Y, Caballero-Oteyza A, Cacheiro P, Carmody L HGG Adv. 2024; 6(1):100371.

PMID: 39394689 PMC: 11564936. DOI: 10.1016/j.xhgg.2024.100371.

A corpus of GA4GH Phenopackets: case-level phenotyping for genomic diagnostics and discovery.

Danis D, Bamshad M, Bridges Y, Cacheiro P, Carmody L, Chong J medRxiv. 2024; .

PMID: 38854034 PMC: 11160806. DOI: 10.1101/2024.05.29.24308104.

Enabling the clinical application of artificial intelligence in genomics: a perspective of the AMIA Genomics and Translational Bioinformatics Workgroup.

Walton N, Nagarajan R, Wang C, Sincan M, Freimuth R, Everman D J Am Med Inform Assoc. 2023; 31(2):536-541.

PMID: 38037121 PMC: 10797281. DOI: 10.1093/jamia/ocad211.

References

Rehm H, Page A, Smith L, Adams J, Alterovitz G, Babb L . GA4GH: International policies and standards for data sharing across genomic research and healthcare. Cell Genom. 2022; 1(2). PMC: 8774288. DOI: 10.1016/j.xgen.2021.100029. View

Malentacchi F, Mancini I, Brandslund I, Vermeersch P, Schwab M, Marc J . Is laboratory medicine ready for the era of personalized medicine? A survey addressed to laboratory directors of hospitals/academic schools of medicine in Europe. Clin Chem Lab Med. 2015; 53(7):981-8. DOI: 10.1515/cclm-2015-0171. View

den Dunnen J, Dalgleish R, Maglott D, Hart R, Greenblatt M, McGowan-Jordan J . HGVS Recommendations for the Description of Sequence Variants: 2016 Update. Hum Mutat. 2016; 37(6):564-9. DOI: 10.1002/humu.22981. View

Wagner A, Babb L, Alterovitz G, Baudis M, Brush M, Cameron D . The GA4GH Variation Representation Specification: A computational framework for variation representation and federated identification. Cell Genom. 2022; 1(2). PMC: 8929418. DOI: 10.1016/j.xgen.2021.100027. View

Holmes J, Moyer E, Phan L, Maglott D, Kattman B . SPDI: data model for variants and applications at NCBI. Bioinformatics. 2019; 36(6):1902-1907. PMC: 7523648. DOI: 10.1093/bioinformatics/btz856. View

Pawliczek P, Patel R, Ashmore L, Jackson A, Bizon C, Nelson T . ClinGen Allele Registry links information about genetic variants. Hum Mutat. 2018; 39(11):1690-1701. PMC: 6519371. DOI: 10.1002/humu.23637. View

Kalman L, Agundez J, Appell M, Black J, Bell G, Boukouvala S . Pharmacogenetic allele nomenclature: International workgroup recommendations for test result reporting. Clin Pharmacol Ther. 2015; 99(2):172-85. PMC: 4724253. DOI: 10.1002/cpt.280. View

Gaedigk A, Whirl-Carrillo M, Pratt V, Miller N, Klein T . PharmVar and the Landscape of Pharmacogenetic Resources. Clin Pharmacol Ther. 2019; 107(1):43-46. PMC: 6925620. DOI: 10.1002/cpt.1654. View

Hess G, Fonseca E, Scott R, Fagerness J . Pharmacogenomic and pharmacogenetic-guided therapy as a tool in precision medicine: current state and factors impacting acceptance by stakeholders. Genet Res (Camb). 2015; 97:e13. PMC: 6863636. DOI: 10.1017/S0016672315000099. View

10.

Abul-Husn N, Obeng A, Sanderson S, Gottesman O, Scott S . Implementation and utilization of genetic testing in personalized medicine. Pharmgenomics Pers Med. 2014; 7:227-40. PMC: 4157398. DOI: 10.2147/PGPM.S48887. View

11.

Stanek E, Sanders C, Taber K, Khalid M, Patel A, Verbrugge R . Adoption of pharmacogenomic testing by US physicians: results of a nationwide survey. Clin Pharmacol Ther. 2012; 91(3):450-8. DOI: 10.1038/clpt.2011.306. View

12.

Lee K, Ma J, Kuo G . Pharmacogenomics: bridging the gap between science and practice. J Am Pharm Assoc (2003). 2010; 50(1):e1-14. DOI: 10.1331/JAPhA.2010.09124. View

13.

Fokkema I, Taschner P, Schaafsma G, Celli J, Laros J, den Dunnen J . LOVD v.2.0: the next generation in gene variant databases. Hum Mutat. 2011; 32(5):557-63. DOI: 10.1002/humu.21438. View

14.

Swen J, Huizinga T, Gelderblom H, de Vries E, Assendelft W, Kirchheiner J . Translating pharmacogenomics: challenges on the road to the clinic. PLoS Med. 2007; 4(8):e209. PMC: 1945038. DOI: 10.1371/journal.pmed.0040209. View

15.

Robarge J, Li L, Desta Z, Nguyen A, Flockhart D . The star-allele nomenclature: retooling for translational genomics. Clin Pharmacol Ther. 2007; 82(3):244-8. DOI: 10.1038/sj.clpt.6100284. View

16.

Sherry S, Ward M, Kholodov M, Baker J, Phan L, Smigielski E . dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2000; 29(1):308-11. PMC: 29783. DOI: 10.1093/nar/29.1.308. View

17.

Relling M, Krauss R, Roden D, Klein T, Fowler D, Terada N . New Pharmacogenomics Research Network: An Open Community Catalyzing Research and Translation in Precision Medicine. Clin Pharmacol Ther. 2017; 102(6):897-902. PMC: 5706548. DOI: 10.1002/cpt.755. View

18.

Escaramis G, Docampo E, Rabionet R . A decade of structural variants: description, history and methods to detect structural variation. Brief Funct Genomics. 2015; 14(5):305-14. DOI: 10.1093/bfgp/elv014. View

19.

Sim S, Altman R, Ingelman-Sundberg M . Databases in the area of pharmacogenetics. Hum Mutat. 2011; 32(5):526-31. PMC: 3352027. DOI: 10.1002/humu.21454. View

20.

Jones D . How personalized medicine became genetic, and racial: Werner Kalow and the formations of pharmacogenetics. J Hist Med Allied Sci. 2011; 68(1):1-48. DOI: 10.1093/jhmas/jrr046. View