SurvBal:对生存结果的组合微生物群平衡
Ying Li1, Teresa Lee2, Kai Marin2
1Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States.
Bioinformatics (Oxford, England)
|October 15, 2024
概括
本研究介绍了SurvBal,这是一种分析微生物组数据和生存结果的工具. 它有助于识别与时间到事件数据相关的细菌平衡,这对生物医学研究至关重要.
科学领域:
- 微生物组研究的研究.
- 统计生物信息学 统计生物信息学
- 对生存分析的分析.
背景情况:
- 分析与健康结果相关的微生物组组成是一个不断发展的领域.
- 确定与疾病进展或治疗反应相关的特定细菌种群或平衡是至关重要的.
- 现有的方法经常与复杂的生存数据作斗争.
研究的目的:
- 推出SurvBal R包和Shiny应用程序用于微生物群存活分析.
- 为了能够选择与时间到事件结果相关的细菌平衡.
- 为微生物组和生物医学领域的研究人员提供一个用户友好的工具.
主要方法:
- 使用考克斯的比例危险和参数生存模型.
- 包含了逐步选择的程序,以确定最佳的微生物平衡.
- 定义微生物平衡为两种类型组之间的相对丰度的几何平均值的比率.
主要成果:
- "SurvBal"有助于识别与生存数据相关的微生物平衡.
- 该包支持对被审查的生存率和时间到事件结果的分析.
- 使研究人员能够探索特定细菌比率与患者存活率之间的关系.
结论:
- SurvBal是微生物组分析研究的宝贵工具,具有生存终点.
- 它解决了在将微生物群落连接到时间到事件数据方面的重大分析差距.
- 该套件提高了发现微生物生物标志物的能力,以预测生存率.
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