BifurcatoR:一个用于揭示临床可操作的信号的框架,在变异中伪装成噪声
bioRxiv : the preprint server for biology
|June 12, 2025
概括
变异异质 (VH) 分析揭示了隐藏的患者子组,以改善疾病治疗. 我们的工具BifurcatoR简化了检测这些亚型,改善了预后和精准医学方法.
科学领域:
- 生物医学数据分析
- 计算生物学是一种计算生物学.
- 统计遗传学 统计遗传学
背景情况:
- 疾病的异质性使医学研究和治疗复杂化.
- 标准分析通常假定人口均性,缺少生物学上不同的患者子组.
- 变异异质 (VH) 提供了一个透镜来检测潜在的病因结构,用于预后和治疗反应.
研究的目的:
- 开发一个可访问的软件平台,用于检测,建模和解释VH.
- 解决现有的VH方法的局限性,包括依赖正常性假设和需要编程专业知识.
- 为VH分析提供研究设计指南.
主要方法:
- 开发了BifurcatoR,这是一个带有Web界面的开源软件平台.
- 基于模拟的综合方法评估和研究设计建议.
- 通过模拟进行基准VH方法,并将BifurcatoR应用于急性髓性白血病 (AML) 和肥胖症数据集.
主要成果:
- VH方法的性能是特定于环境的,取决于数据分布和子组结构.
- 确定了两个不同的AML亚组,治疗反应不同,包括预后较差的EVI1高组.
- 在肥胖中发现的免疫类型亚组与脂肪免疫细胞组成的变化有关.
结论:
- VH代表结构化,临床相关的生物信号,而不是噪音.
- BifurcatoR为将VH纳入生物医学研究提供了一个实用的框架.
- VH分析对生物标志物发现,患者分层和精密医学有影响.
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