Journal Article

CBEA: Competitive balances for taxonomic enrichment analysis

Nguyen, Quang P., Frost, H. Robert, Hoen, Anne G.

2022

Overview

Research in human-associated microbiomes often involves the analysis of taxonomic count tables generated via high-throughput sequencing. It is difficult to apply statistical tools as the data is high-dimensional, sparse, and compositional. An approachable way to alleviate high-dimensionality and sparsity is to aggregate variables into pre-defined sets. Set-based analysis is ubiquitous in the genomics literature and has demonstrable impact on improving interpretability and power of downstream analysis. Unfortunately, there is a lack of sophisticated set-based analysis methods specific to microbiome taxonomic data, where current practice often employs abundance summation as a technique for aggregation. This approach prevents comparison across sets of different sizes, does not preserve inter-sample distances, and amplifies protocol bias. Here, we attempt to fill this gap with a new single-sample taxon enrichment method that uses a novel log-ratio formulation based on the competitive null hypothesis commonly used in the enrichment analysis literature. Our approach, titled competitive balances for taxonomic enrichment analysis (CBEA), generates sample-specific enrichment scores as the scaled log-ratio of the subcomposition defined by taxa within a set and the subcomposition defined by its complement. We provide sample-level significance testing by estimating an empirical null distribution of our test statistic with valid p-values. Herein, we demonstrate, using both real data applications and simulations, that CBEA controls for type I error, even under high sparsity and high inter-taxa correlation scenarios. Additionally, CBEA provides informative scores that can be inputs to downstream analyses such as prediction tasks.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Bias / Biology and Life Sciences / Competition / Computer and Information Sciences / Empirical analysis / Enrichment / Genes / Genetic aspects / Genomes / Genomics / Genomics - methods / High-Throughput Nucleotide Sequencing / Humans / Hypotheses / Identification and classification / Medicine and Health Sciences / Methods / Microbalances / Microbiomes / Microbiota (Symbiotic organisms) / Microbiota - genetics / Next-generation sequencing / Normal distribution / Physical Sciences / Physiological aspects / Research and Analysis Methods / Statistical analysis / Taxa / Taxonomy / Variables