mecoturn: An R package for deciphering microbial turnover patterns along gradients

Abstract

One of the most critical studies on microbial ecology is to reveal microbial turnover patterns along spatial, temporal, or environmental gradients. In such studies, it is often necessary to select appropriate statistical methods based on the experimental design, especially when considering random effects. However, there are few tools that can be readily applied to such cases. In this study, we present a mecoturn R package, designed to support various statistical analyses of microbial turnover along gradients. Two R6 classes (betaturn and taxaturn) have been developed to investigate the beta diversity of microbial communities and the shift profiles of taxonomic abundances, respectively. In each category, several fundamental functions and approaches were encapsulated to enable data preparation, data conversion and filtering, model fitting and visualization. Each analytical component can be implemented with the consideration of random effects, such as (generalized) linear mixed-effects model. Especially in the analysis of beta diversity, the application of linear mixed-effects model fills a gap in the field of related methodologies. To demonstrate the efficacy of two classes and their diverse methodologies, we employed microbial community datasets of bulk soil, rhizosphere soil, and root endophytes of wheat from varying regions of China to conduct a comparative analysis for different pipelines. We found that reasonable analysis considering the heterogeneity of plants can strengthen the reliability of statistical hypothesis testing. The mecoturn package can be freely installed from CRAN (The Comprehensive R Archive Network) or GitHub repository (accessible at: github.com/ChiLiubio/mecoturn).

Graphical abstract

Keywords

beta diversity / ecology / gradient / microbial community / taxonomic abundance

Highlight

	● R mecoturn package is developed for microbial turnover analysis.
	● Linear mixed-effects model is implemented for beta diversity analysis.
	● The shift profiles of taxonomic abundances can be fitted with multiple models.
	● The combination of different approaches can address complex turnover cases.

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