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可扩展的日志比率拉索回归用于使用FLORAL增强微生物特征选择

Teng Fei¹, Tyler Funnell², Nicholas R Waters³

¹Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Cell reports methods

|November 8, 2024

概括

FLORAL是一种用于微生物组分析的新工具,它可以改善对患者结果的生物标志物发现. 它提供了更好的准确性和控制假阳性,特别是在纵向数据.

科学领域:

微生物组研究的研究.
计算生物学是一种计算生物学.
生物统计学生物统计学

背景情况:

确定对患者结果的预测性微生物组生物标志物至关重要,但具有挑战性.
现有的计算方法与复杂的生存终点,纵向样本和测序偏差作斗争.

研究的目的:

推出FLORAL,一个用于微生物组特征选择的开源工具.
为了解决分析复杂生存数据和纵向微生物群样本的现有方法的局限性.

主要方法:

在特征选择中,FLORAL采用可扩展的日志比率拉索回归.
它处理连续,二进制,时间到事件和竞争性风险结果.
该方法将纵向微生物组数据作为时间依赖的共变量纳入,并使用两阶段选过程.

主要成果:

与其他基于拉索的方法相比,FLORAL证明了优异的虚假阳性控制.
它显示出比差异丰度测试方法更好的灵敏度,特别是对于较小的样本大小.
对全原造血细胞移植受体的分析显示,使用纵向数据改善了微生物特征选择.

结论:

FLORAL为微生物组生物标志物发现提供了强大且可扩展的解决方案.
该工具有效地整合了纵向微生物群数据,以提高预测准确度.
佛罗拉尔在微生物组数据分析复杂患者结果方面取得了进展.

关键词:

CP: 微生物学微生物学 CP:系统生物学系统生物学组成数据组合数据.拉索 (Lasso) 是一个拉索.纵向数据纵向数据纵向数据微生物组是一个微生物组.生存分析,生存分析.选择变量的选择变量.

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