title: Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine.
abstract: Advances in genomic medicine have the potential to change the way we treat human disease, but translating these advances into reality for improving healthcare outcomes depends essentially on our ability to discover disease- and/or drug-associated clinically actionable genetic mutations. Integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a big data infrastructure can provide an efficient and effective way to identify clinically actionable genetic variants for personalized treatments and reduce healthcare costs. We review bioinformatics processing of next-generation sequencing (NGS) data, bioinformatics infrastructures for implementing precision medicine, and bioinformatics approaches for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.
authors.affiliation: Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.
authors.forename: Tonia C
authors.initials: TC
authors.lastname: Carter
authors.affiliation: Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI 54449, USA.|Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors.forename: Max M
authors.initials: MM
authors.lastname: He
mesh_terms: D019295:Computational Biology; D057286:Electronic Health Records; D014644:Genetic Variation; D015894:Genome, Human / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D008490:Medical Informatics; D058990:Molecular Targeted Therapy; D057285:Precision Medicine