Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L 2 UniFrac.
Finding phylogeny-aware and biologically meaningful averages of metagenomic samples: L 2 UniFrac.
复制标题
寻找宏基因组样本的系统发育感知和生物学意义的平均值：L 2 UniFrac。
DOI：
10.1101/2023.02.02.526854
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Koslicki,David
中科院分区：
文献类型：
--
作者：
Wei,Wei;Millward,Andrew;Koslicki,David
动机宏基因组样本具有很高的时空变异性。因此，以生物学上合理且可解释的方式总结和表征给定环境的微生物组成是有用的。 UniFrac 指标是一种稳健且广泛使用的指标，用于测量宏基因组样本之间的变异性。我们建议，可以通过查找样本中关于 UniFrac 距离的平均值（也称为重心）来改进宏基因组环境的表征。然而，这样的 UniFrac 平均值可能包含负条目，使其不再是宏基因组群落的有效表示。结果为了克服这一内在问题，我们提出了 UniFrac 度量的特殊版本，称为 L2UniFrac，它继承了传统 UniFrac 的系统发育性质，并且可以轻松计算平均值，产生具有生物学意义的特定环境“代表性样本”。我们展示了此类代表性样本的有用性以及 L2UniFrac 在宏基因组样本的有效聚类中的扩展用途，并为 L2UniFrac 的所需属性提供数学表征和证明。可用性和实现 https://github.com/KoslickiLab/L2-UniFrac.git 提供了原型实现。所有图形、数据和分析均可在 https://github.com/KoslickiLab/L2-UniFrac-Paper 上复制
MotivationMetagenomic samples have high spatiotemporal variability. Hence, it is useful to summarize and characterize the microbial makeup of a given environment in a way that is biologically reasonable and interpretable. The UniFrac metric has been a robust and widely used metric for measuring the variability between metagenomic samples. We propose that the characterization of metagenomic environments can be improved by finding the average, a.k.a. the barycenter, among the samples with respect to the UniFrac distance. However, it is possible that such a UniFrac-average includes negative entries, making it no longer a valid representation of a metagenomic community.ResultsTo overcome this intrinsic issue, we propose a special version of the UniFrac metric, termedL2UniFrac, which inherits the phylogenetic nature of the traditional UniFrac and with respect to which one can easily compute the average, producing biologically meaningful environment-specific “representative samples.” We demonstrate the usefulness of such representative samples as well as the extended usage ofL2UniFrac in efficient clustering of metagenomic samples, and provide mathematical characterizations and proofs to the desired properties ofL2UniFrac.Availability and implementationA prototype implementation is provided at https://github.com/KoslickiLab/L2-UniFrac.git. All figures, data, and analysis can be reproduced at https://github.com/KoslickiLab/L2-UniFrac-Paper