• MicrobiotaProcess defines an MPSE structure to better integrate both primary and intermediate microbiome datasets.
• MicrobiotaProcess improves the integration and exploration of downstream data analysis.
• MicrobiotaProcess provides a set of functions under a unified tidy framework, which helps users explore related datasets more efficiently.
• MicrobiotaProcess offers many visual methods to quickly render clear and comprehensive visualizations that reveal meaningful insights.

The structure of the MPSE class.

The Overview of the design of MicrobiotaProcess package

Shuangbin Xu and Guangchuang Yu

School of Basic Medical Sciences, Southern Medical University

If you use MicrobiotaProcess in published research. Please cite the paper:

Shuangbin Xu, Li Zhan, Wenli Tang, Qianwen Wang, Zehan Dai, Land Zhou, Tingze Feng, Meijun Chen, Tianzhi Wu, Erqiang Hu, Guangchuang Yu^*. MicrobiotaProcess: A comprehensive R package for deep mining microbiome. The Innovation. 2023, 4(2):100388. doi: 10.1016/j.xinn.2023.100388.

• Source code to produce Supplementary Material

Get the released version from Bioconductor:

## try http:// if https:// URLs are not supported ## the url of mirror
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
## BiocManager::install("BiocUpgrade") ## you may need this
BiocManager::install("MicrobiotaProcess")

the development version from github:

if (!requireNamespace("remotes", quietly=TRUE))
    install.packages("remotes")
remotes::install_github("YuLab-SMU/MicrobiotaProcess")

For more details, please refer to the online vignette.

We welcome any contributions! By participating in this project you agree to abide by the terms outlined in the Contributor Code of Conduct.