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Review
. 2016:2016:3617572.
doi: 10.1155/2016/3617572.

Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine

Tonia C Carter  1 , Max M He  1   2   3
Affiliations
Review

Challenges of Identifying Clinically Actionable Genetic Variants for Precision Medicine

Tonia C Carter et al. J Healthc Eng. 2016.

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.

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Conflict of interest statement

The authors indicated no potential competing interests.

Figures

Figure 1
Figure 1
A flow chart of processing next-generation sequencing data.
Figure 2
Figure 2
The basic framework of SeqHBase for detecting clinically actionable genetic variants.
Figure 3
Figure 3
Overview of steps for a laboratory to obtain accreditation by the College of American Pathologists.
Figure 4
Figure 4
Elements of a proposed infrastructure for bioinformatics processing of sequencing data in clinical laboratories.
Figure 5
Figure 5
Cloud computing diagram.
See this image and copyright information in PMC

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