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一种用于药物遗传学分析的新型云原生工具。

A New Cloud-Native Tool for Pharmacogenetic Analysis.

机构信息

European Nucleotide Archive, European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, Cambridge CB10 1SD, UK.

Department of Bioinformatics and Computational Biology, Faculty of Arts and Science, University of Toronto, Toronto, ON M5S 3G3, Canada.

出版信息

Genes (Basel). 2024 Mar 11;15(3):352. doi: 10.3390/genes15030352.

Abstract

BACKGROUND

The advancement of next-generation sequencing (NGS) technologies provides opportunities for large-scale Pharmacogenetic (PGx) studies and pre-emptive PGx testing to cover a wide range of genotypes present in diverse populations. However, NGS-based PGx testing is limited by the lack of comprehensive computational tools to support genetic data analysis and clinical decisions.

METHODS

Bioinformatics utilities specialized for human genomics and the latest cloud-based technologies were used to develop a bioinformatics pipeline for analyzing the genomic sequence data and reporting PGx genotypes. A database was created and integrated in the pipeline for filtering the actionable PGx variants and clinical interpretations. Strict quality verification procedures were conducted on variant calls with the whole genome sequencing (WGS) dataset of the 1000 Genomes Project (G1K). The accuracy of PGx allele identification was validated using the WGS dataset of the Pharmacogenetics Reference Materials from the Centers for Disease Control and Prevention (CDC).

RESULTS

The newly created bioinformatics pipeline, Pgxtools, can analyze genomic sequence data, identify actionable variants in 13 PGx relevant genes, and generate reports annotated with specific interpretations and recommendations based on clinical practice guidelines. Verified with two independent methods, we have found that Pgxtools consistently identifies variants more accurately than the results in the G1K dataset on GRCh37 and GRCh38.

CONCLUSIONS

Pgxtools provides an integrated workflow for large-scale genomic data analysis and PGx clinical decision support. Implemented with cloud-native technologies, it is highly portable in a wide variety of environments from a single laptop to High-Performance Computing (HPC) clusters and cloud platforms for different production scales and requirements.

摘要

背景

下一代测序(NGS)技术的进步为大规模药物遗传学(PGx)研究和预防性 PGx 测试提供了机会,以涵盖不同人群中存在的广泛基因型。然而,基于 NGS 的 PGx 测试受到缺乏全面的计算工具来支持遗传数据分析和临床决策的限制。

方法

专门用于人类基因组学的生物信息学实用程序和最新的基于云的技术被用于开发一个生物信息学管道,用于分析基因组序列数据并报告 PGx 基因型。创建了一个数据库并将其集成到管道中,用于过滤可操作的 PGx 变体和临床解释。在对 1000 基因组计划(G1K)的全基因组测序(WGS)数据集进行严格的质量验证程序后,对变体调用进行了验证。使用疾病预防控制中心(CDC)的药物遗传学参考材料的 WGS 数据集验证了 PGx 等位基因识别的准确性。

结果

新创建的生物信息学管道 Pgxtools 可以分析基因组序列数据,识别 13 个 PGx 相关基因中的可操作变体,并根据临床实践指南生成带有特定解释和建议的报告。通过两种独立的方法进行验证,我们发现 Pgxtools 始终比 G1K 数据集在 GRCh37 和 GRCh38 上更准确地识别变体。

结论

Pgxtools 提供了一个用于大规模基因组数据分析和 PGx 临床决策支持的集成工作流程。它采用云原生技术实现,可从单个笔记本电脑到高性能计算(HPC)集群和云平台,在各种环境中高度便携,适用于不同的生产规模和需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6209/10969787/fc31cc0be1de/genes-15-00352-g001.jpg

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