John Sumi Elsa, Channanath Arshad Mohamed, Hebbar Prashantha, Nizam Rasheeba, Thanaraj Thangavel Alphonse, Al-Mulla Fahd
Genetics & Bioinformatics, Dasman Diabetes Institute, 15462 Dasman, Kuwait.
J Pers Med. 2021 Mar 16;11(3):210. doi: 10.3390/jpm11030210.
With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug-genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive easy-to-use interface. PharmaKU can help to overcome several hurdles posed by previous pharmacogenomics tools, including input in hg38 format only, while hg19/GRCh37 is now the most popular reference genome assembly among clinicians and geneticists, as well as the lack of clinical recommendations and other pertinent dosage-related information. This tool extracts genetic variants from nine well-annotated pharmacogenes (for which diplotype to phenotype information is available) from whole genome variant files and uses Stargazer software to assign diplotypes and apply prescribing recommendations from pharmacogenomic resources. The tool is wrapped with a user-friendly web interface, which allows for choosing hg19 or hg38 as the reference genome version and reports results as a comprehensive PDF document. PharmaKU is anticipated to enable bench to bedside implementation of pharmacogenomics knowledge by bringing precision medicine closer to a clinical reality.
随着药物基因组学领域基因组测序技术的巨大进步，必须使数据能够被更广泛的临床学科更有效地利用。需要药物-基因组相互作用组信息的医生，一直受到基于复杂的药物基因组学星型分类系统的挑战。我们在此展示了一个基于网络的端到端药物基因组学工具PharmaKU，它具有全面且易于使用的界面。PharmaKU有助于克服先前药物基因组学工具带来的几个障碍，包括仅支持hg38格式输入，而hg19/GRCh37目前是临床医生和遗传学家中最常用的参考基因组组装版本，以及缺乏临床建议和其他相关剂量信息。该工具从全基因组变异文件中提取来自九个注释完善的药物基因（可获得双倍型到表型信息）的遗传变异，并使用Stargazer软件分配双倍型，并应用来自药物基因组学资源的处方建议。该工具包装有用户友好的网络界面，允许选择hg19或hg38作为参考基因组版本，并以全面的PDF文档形式报告结果。预计PharmaKU将通过使精准医学更接近临床现实，实现药物基因组学知识从实验室到床边的应用。
