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零不是缺席:基于审查的微生物组数据差异丰度分析

Lap Sum Chan¹, Gen Li¹

¹Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, United States.

Bioinformatics (Oxford, England)

|February 8, 2024

概括

一种新的方法,即基于审查的微生物组比例分析 (CAMP),解决了微生物组数据的零稀疏性问题. CAMP 改进了差异丰度分析,提高了微生物组研究的统计能力和准确性.

科学领域:

微生物学微生物学
生物信息学是一种生物信息学.
统计遗传学统计遗传学

背景情况:

微生物组数据分析受到稀疏性的挑战,许多零数.
过度的零违反了差异丰度分析中的假设,增加了I型错误并减少了功率.

研究的目的:

引入一种新的规范化方法,CAMP,以解决微生物组数据的稀疏性.
为了实现生存分析技术的应用,改进差异丰度分析.

主要方法:

开发了基于审查的微生物组比例分析 (CAMP).
将零点视为被审查的观察结果,将数据转化为无绑定时间到事件的数据.
使用生存分析技术,包括考克斯的比例危险模型.

主要成果:

在模拟中,CAMP展示了适当的I型错误控制和高统计能力.
在人类肠道微生物组数据集中确定了60种新的差异丰富的种类.
CAMP有效地克服了微生物组数据分析中的稀疏性挑战.

结论:

在稀疏的微生物组数据中,CAMP提供了一种强大的差异丰度分析方法.
该方法增强了统计能力,并为微生物组组成提供了宝贵的见解.
为了更广泛的应用,CAMP可以作为R包提供.

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