microeco 2: A comprehensive R package for downstream analysis of microbiome omics data

Abstract

Efficient downstream analysis of microbiome data remains a major challenge for researchers. Since its initial release in late 2020, the R microeco package has been widely used for downstream statistical analysis and visualization of omics data, such as amplicon sequencing. Compared with its initial release, the current second version of the microeco package has undergone extensive updates and enhancements. The key upgrades include: (1) The addition of classes for data normalization and machine learning, respectively; (2) The incorporation of additional analytical methods and the addition of functions across various classes; (3) Optimization of the parameter system to expand the applicable scenarios of relevant methods; (4) Code restructuring to enhance the connectivity between statistical analysis and visualization within each class; (5) Extension of certain functions to enable the analysis of abundance data in complex formats generated from bioinformatic analyses of metagenomic/metatranscriptomic data; (6) Incorporation of several analytical methods commonly used in transcriptomic and metabolomic data analyses. Overall, the microeco package 2.0 offers broader method coverage and a wider range of application scenarios compared to the previous version and other existing R packages. The steady growth in user downloads demonstrates that the microeco package, which is built on R6 (a class-based object-oriented programming system for R), has established a broad and active user base. The second version of the microeco R package is open-source and available on the Comprehensive R Archive Network and GitHub (https://github.com/ChiLiubio/microeco).

Keywords

data normalization / diversified methods / function refactoring / machine learning metagenomics

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