Phylogeny-guided microbiome OTU-specific association test (POST)

Abstract

Background: The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high dimensionality and sparsity of typical microbiome profiles. Phylogenetic information is often incorporated to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effects of microbes, and phylogenetic information should be incorporated in a data-supervised fashion.

Results: In this work, we propose a local collapsing test called phylogeny-guided microbiome OTU-specific association test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenetic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community level to OTU level. Using simulation studies, we show that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, in real data applications on bacterial vaginosis and on preterm birth, we find that POST can identify similar or more outcome-associated OTUs that are of biological relevance compared to existing methods.

Conclusions: Using POST, we show that adaptively leveraging the phylogenetic information can enhance the selection performance of associated microbiome features by improving the overall true-positive and false-positive detection. We developed a user friendly R package POSTm which is freely available on CRAN ( https://CRAN.R-project.org/package=POSTm ). Video Abstract.

Keywords: Association test; Kernel machine regression; Phylogenetic tree.

Fig. 1

Overview of phylogeny-guided microbiome OTU-specific association test (POST)

Fig. 2

A Phylogenetic relationship between the target OTU (OTU3438) and its neighboring OTUs. B OTU phylogenetic correlation r_ℓm under different values of the tuning parameter c, illustrated by setting m = OTU3438 as the target OTU. The x-axis is the OTUs shown in the same order as the tree tips. The y-axis is r_ℓm, the correlation between OTU3438 and the remaining OTUs

Fig. 3

Illustration of the five causal OTU scenarios considered in the simulation. Scenarios 1 to 3 consider larger “causal hubs,” each containing about 7–10 causal OTUs; scenario 4 considers smaller causal hubs of 2–3 causal OTUs; scenario 5 considers causal OTUs with random positions in the phylogenetic tree. Red (blue) circles indicate that causal effect size tends to be positive (negative)

Fig. 4

ROC curves of simulation A with large OTU effect size (top row) and small OTU effect size (bottom row) for POST, Single-OTU test (SO), TreeFDR (TF), DESeq2 (DE), ANCOM-BC (AB), LinDA (DA), and Wilcoxon rank-sum test (WR) under the 5 causal scenarios. Scenarios 1 to 3 consider larger “causal hubs,” each containing about 7–10 causal OTUs; scenario 4 considers smaller causal hubs of 2–3 causal OTUs; scenario 5 considers causal OTUs with random positions in the phylogenetic tree

Fig. 5

Upset plot of detected OTUs at FDR level of 0.05 and phylogenetic trees of the analyzed OTUs with detected OTUs for bacterial vaginosis study. SO, single-OTU test implemented by POST with c = 0; TF, TreeFDR; DE, DESeq2; AB, ANCOM-BC; LD, LinDA; WR-P, Wilcoxon rank-sum test using proportional data; WR-R, Wilcoxon rank-sum test using CLR transformed data

Fig. 6

Upset plot of detected OTUs at FDR level of 0.05 and phylogenetic trees of the analyzed OTUs with detected OTUs for preterm birth study. SO, Single-OTU test implemented by POST with c = 0; TF, TreeFDR; DE, DESeq2; AB, ANCOM-BC; LD, LinDA; WR-P, Wilcoxon rank-sum test using proportional data; WR-R,Wilcoxon rank-sum test using the CLR transformed data