Suppr超能文献

基因分型工具的基准测试:短读测序样本的性能分析和深度相关评估。

Benchmarking pharmacogenomics genotyping tools: Performance analysis on short-read sequencing samples and depth-dependent evaluation.

机构信息

Cancer Therapies, Stem Cell Medicine, Murdoch Children's Research Institute, Parkville, Victoria, Australia.

Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.

出版信息

Clin Transl Sci. 2024 Aug;17(8):e13911. doi: 10.1111/cts.13911.

Abstract

Pharmacogenomics (PGx) investigates the influence of genetics on drug responses, enabling tailored treatments for personalized healthcare. This study assessed the accuracy of genotyping six genes using whole genome sequencing with four different computational tools and various sequencing depths. The effects of using different reference genomes (GRCh38 and GRCh37) and sequence aligners (BWA-MEM and Bowtie2) were also explored. The results showed generally minor variations in tool performance across most genes; however, more notable discrepancies were observed in the analysis of the complex CYP2D6 gene. Cyrius, a CYP2D6-specific tool, demonstrated the most robust performance, achieving the highest concordance rates for CYP2D6 in all instances, comparable to the consensus approach in most cases. There were rather small differences between the samples with 20× coverage depth and those with higher depth, but the decreased performance was more evident at lower depths, particularly at 5×. Additionally, variations in CYP2D6 results were observed when samples were aligned to different reference genomes using the same method, or to the same genome using different aligners, which led to reporting incorrect rare star alleles in several cases. These findings inform the selection of optimal PGx tools and methodologies as well as suggest that employing a consensus approach with two or more tools might be preferable for certain genes and tool combinations, especially at lower sequencing depths, to ensure accurate results. Additionally, we show how the upstream alignment can affect the performance of tools, an important factor to take into account.

摘要

药物基因组学(PGx)研究遗传对药物反应的影响,为个性化医疗提供针对性治疗。本研究评估了使用全基因组测序和四种不同的计算工具以及不同测序深度对六个基因进行基因分型的准确性。还探讨了使用不同参考基因组(GRCh38 和 GRCh37)和序列比对器(BWA-MEM 和 Bowtie2)的效果。结果表明,大多数基因的工具性能普遍存在较小差异;然而,在分析复杂的 CYP2D6 基因时,观察到更明显的差异。Cyprius 是一种 CYP2D6 特异性工具,表现出最稳健的性能,在所有情况下都实现了 CYP2D6 的最高一致性率,与大多数情况下的共识方法相当。在 20×覆盖深度的样本和更高深度的样本之间存在较小的差异,但在较低的深度下性能下降更为明显,尤其是在 5×时。此外,当使用相同的方法将样本与不同的参考基因组对齐,或使用不同的对齐器将样本与同一基因组对齐时,观察到 CYP2D6 结果的变化,这导致在几种情况下报告不正确的罕见星等位基因。这些发现为选择最佳 PGx 工具和方法提供了信息,并表明在某些基因和工具组合中,特别是在较低的测序深度下,采用两种或更多工具的共识方法可能更为可取,以确保准确的结果。此外,我们展示了上游对齐如何影响工具的性能,这是一个需要考虑的重要因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/725d/11315677/23bece56fef2/CTS-17-e13911-g002.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验