College of Computer Science and Technology, Qingdao University, Qingdao, China.
Bioinformatics. 2023 Apr 3;39(4). doi: 10.1093/bioinformatics/btad148.
Beta-diversity quantitatively measures the difference among microbial communities thus enlightening the association between microbiome composition and environment properties or host phenotypes. The beta-diversity analysis mainly relies on distances among microbiomes that are calculated by all microbial features. However, in some cases, only a small fraction of members in a community plays crucial roles. Such a tiny proportion is insufficient to alter the overall distance, which is always missed by end-to-end comparison. On the other hand, beta-diversity pattern can also be interfered due to the data sparsity when only focusing on nonabundant microbes.
Here, we develop Flex Meta-Storms (FMS) distance algorithm that implements the "local alignment" of microbiomes for the first time. Using a flexible extraction that considers the weighted phylogenetic and functional relations of microbes, FMS produces a normalized phylogenetic distance among members of interest for microbiome pairs. We demonstrated the advantage of FMS in detecting the subtle variations of microbiomes among different states using artificial and real datasets, which were neglected by regular distance metrics. Therefore, FMS effectively discriminates microbiomes with higher sensitivity and flexibility, thus contributing to in-depth comprehension of microbe-host interactions, as well as promoting the utilization of microbiome data such as disease screening and prediction.
FMS is implemented in C++, and the source code is released at https://github.com/qdu-bioinfo/flex-meta-storms.
β多样性定量衡量微生物群落之间的差异，从而揭示微生物组组成与环境特性或宿主表型之间的关联。β多样性分析主要依赖于微生物组之间的距离，这些距离是通过所有微生物特征计算得出的。然而，在某些情况下，群落中的一小部分成员起着至关重要的作用。这样的小比例不足以改变整体距离，而这一点总是被端到端的比较所忽略。另一方面，当只关注非丰富微生物时，由于数据稀疏性，β多样性模式也可能受到干扰。
在这里，我们开发了 Flex Meta-Storms（FMS）距离算法，该算法首次实现了微生物组的“局部比对”。使用一种灵活的提取方法，该方法考虑了微生物的加权系统发育和功能关系，FMS 为微生物对之间的感兴趣成员生成了归一化的系统发育距离。我们使用人工和真实数据集证明了 FMS 在检测不同状态下微生物组之间细微变化方面的优势，这些变化被常规距离度量所忽略。因此，FMS 能够有效地以更高的灵敏度和灵活性来区分微生物组，从而有助于深入理解微生物-宿主相互作用，并促进微生物组数据的利用，如疾病筛查和预测。
FMS 是用 C++实现的，源代码在 https://github.com/qdu-bioinfo/flex-meta-storms 上发布。
