Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs

Frontiers in Medicine

article

Matt A. Field¹ 

[1] Centre for Tropical Bioinformatics and Molecular Biology, College of Public Health, Medical and Veterinary Science, James Cook University;Immunogenomics Lab, Garvan Institute of Medical Research;Menzies School of Health Research, Charles Darwin University

关键词: precision medicine;    variant detection;    high-throughput sequencing;    pathogenic variant;    variant prioritization;    FPGA—field-programmable gate array;    GPU-accelerated;   

DOI  :  10.3389/fmed.2022.806696

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Precision medicine programs to identify clinically relevant genetic variation have been revolutionized by access to increasingly affordable high-throughput sequencing technologies. A decade of continual drops in per-base sequencing costs means it is now feasible to sequence an individual patient genome and interrogate all classes of genetic variation for < $1,000 USD. However, while advances in these technologies have greatly simplified the ability to obtain patient sequence information, the timely analysis and interpretation of variant information remains a challenge for the rollout of large-scale precision medicine programs. This review will examine the challenges and potential solutions that exist in identifying predictive genetic biomarkers and pharmacogenetic variants in a patient and discuss the larger bioinformatic challenges likely to emerge in the future. It will examine how both software and hardware development are aiming to overcome issues in short read mapping, variant detection and variant interpretation. It will discuss the current state of the art for genetic disease and the remaining challenges to overcome for complex disease. Success across all types of disease will require novel statistical models and software in order to ensure precision medicine programs realize their full potential now and into the future.

【 授权许可】

CC BY