ZINQ-L:用于对纵向微生物群数据的差异性丰度分析的零膨胀量子式方法
Shuai Li1, Runzhe Li1, John R Lee2,3
1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Frontiers in genetics
|February 13, 2025
概括
我们开发了一种新的方法,用于纵向 (ZINQ-L) 微生物组分析的零膨胀量子方法,以准确地识别随着时间的推移与健康状况相关的细菌种群. 这种方法提高了功率,并控制了复杂微生物组数据中的错误发现.
科学领域:
- 微生物组研究的研究.
- 统计遗传学 统计遗传学
- 计算生物学是一种计算生物学.
背景情况:
- 微生物组分析对于了解疾病机制和随时间推移的治疗效果至关重要.
- 纵向微生物组数据提出了诸如稀疏性,过度分散性和主体内相关性等挑战.
- 现有的方法通常依赖于限制性分布假设,导致错误发现率膨胀,无法检测异质关联.
研究的目的:
- 开发一种可靠的统计方法,用于在纵向微生物组研究中进行差异丰度测试.
- 解决处理复杂微生物组数据分布和识别异质关联的现有方法的局限性.
主要方法:
- 为纵向 (ZINQ-L) 微生物组分析提出了零膨胀量的方法.
- 在假设测试中采用混合效应的量级等级得分测试.
- 纳入了存在-缺席状态的后勤模型和为零通货膨胀调整的定量测试.
- 采用回归方法,对强度进行最小的分布假设.
主要成果:
- 在模拟研究中,ZINQ-L在检测真信号方面表现出更强的功率.
- 该方法有效控制了错误发现率.
- 在移植微生物组研究中的应用验证了其性能.
结论:
- ZINQ-L提供了一种强大而强大的方法,用于识别与纵向微生物组研究结果相关的种类.
- 它通过提供灵活性和提高功率来补充现有方法.
- 该方法增强了对健康和疾病中的微生物群与宿主相互作用的理解.
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