对用于检测微卫星不稳定的计算工具的性能评估
Harrison Anthony1,2, Cathal Seoighe1,2
1School of Mathematical and Statistical Sciences, University of Galway, Galway H91 TK33, Ireland.
Briefings in bioinformatics
|August 12, 2024
概括
微卫星不稳定性 (MSI) 分析的计算工具在不同的测序类型中显示了可变的性能. 基准测试显示,MSI工具可能在与原始评估不匹配的数据上表现不佳,这会影响癌症生物标志物应用.
科学领域:
- 基因组学就是基因组学.
- 癌症研究 癌症研究
- 生物信息学是一种生物信息学.
背景情况:
- 微卫星不稳定性 (MSI) 是指导各种癌症免疫检查点抑制剂治疗的关键生物标志物.
- 计算工具对于使用下一代测序数据将样品分类为高MSI或微卫星稳定性至关重要.
- 现有的MSI工具往往缺乏明确的使用指南和独立的性能基准.
研究的目的:
- 综合评估和比较领先的MSI计算工具的性能.
- 评估各种测序数据类型的工具性能,包括整个外体,整个基因组,基因面板和RNA测序.
- 确定可靠的MSI工具用于临床应用,并指导未来的开发.
主要方法:
- 通过使用多个独特数据集评估了八个突出的MSI预测工具.
- 对整个外因组测序 (WES),整个基因组测序 (WGS),基因组和RNA测序 (RNA-Seq) 数据进行比较的工具性能.
- 使用接收器操作特征 (ROC) 和曲线下的精度回忆面积 (AUC) 度量评估性能,并评估了工具间协议.
主要成果:
- 大多数MSI工具在WES数据上复制了原始发现,但在WGS数据上表现较差.
- 与商业软件相比,在基因组数据上的工具协议和性能中观察到显著的差异.
- 对于MSI分类的最佳值截止值因排序类型而异.
- 特定于RNA-Seq的MSI工具的性能优于基于DNA的工具,甚至DNA工具在组合不同的数据集时也显示出精度下降.
结论:
- 当MSI工具应用于与其原始评估队列不同的数据集时,其性能可能会显著降低.
- 由于潜在的性能限制,建议在WGS或RNA-Seq数据以及组合数据集上使用MSI工具时谨慎使用.
- MSIsensor2和MANTIS在大多数数据集中显示出强大的性能,但在汇总所有数据时精度降低,突出显示了需要仔细选择和验证工具的必要性.
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