@article{7886bc1041274384aa539e66d7d303b1,
title = "Development and application of a computable genotype model in the GA4GH Variation Representation Specification",
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.",
keywords = "Allele, GA4GH, Genomics, Genotype, Haplotype, HGVS, VCF, VRS",
author = "Wesley Goar and Lawrence Babb and Srikar Chamala and Melissa Cline and Freimuth, {Robert R.} and Hart, {Reece K.} and Kori Kuzma and Jennifer Lee and Tristan Nelson and Andreas Prli{\'c} and Kevin Riehle and Anastasia Smith and Kathryn Stahl and Yates, {Andrew D.} and Rehm, {Heidi L.} and Wagner, {Alex H.}",
note = "Funding Information: Acknowledgments The authors thank Li Gong, Teri E. Klein, Ryan Whaley, and Michelle Whirl-Carillo (Stanford University) for important discussions and critical feedback that substantially advanced this work. WAG & AHW were supported by the National Human Genome Research Institute (NHGRI) award R35HG011949. LB & HR were supported by the NHGRI award U24HG006834. MSC was supported by the National Cancer Institute (NCI) award U01CA242954-01. RRF & KR were supported by the NHGRI award U41HG006834. RRF was supported by the NHGRI award R35HG011899. KR was supported by the NHGRI awards U41HG009649, U41HG009650. ADY was supported by the Wellcome Trust [WT222155/Z/20/Z] and the European Molecular Biology Laboratory. RKH was supported by ClinGen, Invitae, Inc, and MyOme, Inc. Funding Information: The authors thank Li Gong, Teri E. Klein, Ryan Whaley, and Michelle Whirl-Carillo (Stanford University) for important discussions and critical feedback that substantially advanced this work. WAG & AHW were supported by the National Human Genome Research Institute (NHGRI) award R35HG011949. LB & HR were supported by the NHGRI award U24HG006834. MSC was supported by the National Cancer Institute (NCI) award U01CA242954-01. RRF & KR were supported by the NHGRI award U41HG006834. RRF was supported by the NHGRI award R35HG011899. KR was supported by the NHGRI awards U41HG009649, U41HG009650. ADY was supported by the Wellcome Trust [WT222155/Z/20/Z] and the European Molecular Biology Laboratory. RKH was supported by ClinGen, Invitae, Inc, and MyOme, Inc. Publisher Copyright: {\textcopyright} 2022 The Authors.; 28th Pacific Symposium on Biocomputing, PSB 2023 ; Conference date: 03-01-2023 Through 07-01-2023",
year = "2023",
doi = "10.1142/9789811270611_0035",
language = "English (US)",
pages = "383--394",
journal = "Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing",
issn = "2335-6936",
number = "2023",
}