Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs
Field, Matt A. (2022) Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs. Frontiers in Medicine, 9. 806696.
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Abstract
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.
| Item ID: | 74538 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2296-858X |
| Keywords: | FPGA—field-programmable gate array, GPU-accelerated, high-throughput sequencing, pathogenic variant, precision medicine, variant detection, variant prioritization |
| Copyright Information: | © 2022 Field. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Funders: | National Health and Medical Research Council (NHMRC) |
| Projects and Grants: | NHMRC research fellowship APP5121190 |
| Date Deposited: | 14 Jun 2022 04:37 |
| FoR Codes: | 31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310208 Translational and applied bioinformatics @ 100% |
| SEO Codes: | 20 HEALTH > 2001 Clinical health > 200101 Diagnosis of human diseases and conditions @ 100% |
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