# microeco

**Repository Path**: chiliubio/microeco

## Basic Information

- **Project Name**: microeco
- **Description**: An R package for data mining in microbial community ecology
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: http://gitee.com/chiliubio/microeco
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2022-03-20
- **Last Updated**: 2026-05-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# microeco <a href="https://chiliubio.github.io/microeco_tutorial/"><img src="./inst/logo.png" width=150 align="right" ></a>

An R package for data mining in microbial community ecology

[![CRAN](https://www.r-pkg.org/badges/version/microeco)](https://cran.r-project.org/web/packages/microeco/index.html)
[![CRAN](https://cranlogs.r-pkg.org/badges/grand-total/microeco)](https://cran.r-project.org/web/packages/microeco/index.html)
![](https://img.shields.io/badge/Release-2.1.0-orange.svg) ![](https://img.shields.io/badge/Test-2.1.1-red.svg)

## Background
The increasing volume and complexity of microbiome omics data pose a challenge for the downstream data analysis. 
Although numerous R packages exist in this field, 
it remains difficult to perform data mining in an efficient and comprehensive manner. 
Therefore, we developed the R microeco package (abbreviated and pronounced as **_[miːkəu]_**).


## Main Features
  + R6 Class to store and analyze data: flexible and modularized
  + Data preprocessing and normalization
  + Taxonomic abundance visualization
  + Venn diagram
  + Alpha diversity
  + Beta diversity
  + Differential abundance test
  + Machine learning
  + Null model analysis
  + Network analysis
  + Environmental data analysis
  + Functional prediction
  + Metabolite origin inference

## Install R/RStudio
If you do not already have R/RStudio installed, follow these steps:

1. Install [R](https://www.r-project.org/)
2. Install [RStudio](https://posit.co/downloads/)

Open RStudio -> Tools -> Global Options -> Packages, select the appropriate mirror in Primary CRAN repository.

## Install microeco

Install microeco package from CRAN.

```r
install.packages("microeco")
```

Or install the latest development version from Github.

```r
# If devtools package is not installed, first install it
install.packages("devtools")
devtools::install_github("ChiLiubio/microeco")
```


## Tutorial
A detailed online **tutorial** (https://chiliubio.github.io/microeco_tutorial/) is provided with the package.
For offline use, the tutorial can also be downloaded and opened locally (https://github.com/ChiLiubio/microeco_tutorial/releases).
To view these links in an R session, run `?microeco`.
Please use a class name to search for its help document (e.g., `?microtable`) rather than searching for individual functions therein.
Before creating a new issue in the [Issues](https://github.com/ChiLiubio/microeco/issues), 
please read the guideline (https://chiliubio.github.io/microeco_tutorial/notes.html#github-issues).
To create a basic microtable object directly from outputs of other tools/platforms (e.g. QIIME2, HUMAnN, Kraken2 and phyloseq), 
please use the `file2meco` package (https://github.com/ChiLiubio/file2meco).
To help users familiarize themselves with the package using multi-omics data,
we also provide a systematic protocol (https://github.com/ChiLiubio/microeco_protocol_v1).


## Citation
Chi Liu, Felipe R. P. Mansoldo, Hankang Li, Alane Beatriz Vermelho, Raymond Jianxiong Zeng, Xiangzhen Li & Minjie Yao. 
A workflow for statistical analysis and visualization of microbiome omics data using the R microeco package. 
**Nature Protocols**, 21: 1300–1324 (2026). https://doi.org/10.1038/s41596-025-01239-4

Chi Liu, Yaoming Cui, Xiangzhen Li and Minjie Yao. _microeco_: an R package for data mining in microbial community ecology.
**FEMS Microbiology Ecology**, 97(2): fiaa255 (2021). https://doi.org/10.1093/femsec/fiaa255


## Contributing

We welcome any contribution, including but not limited to code, idea and [tutorial](https://chiliubio.github.io/microeco_tutorial/).
Please report errors and questions on Github [Issues](https://github.com/ChiLiubio/microeco/issues).
Any contribution via [Pull requests](https://github.com/ChiLiubio/microeco/pulls) will be appreciated.
By participating in this project you agree to abide by the terms outlined in the [Contributor Code of Conduct](CODE_OF_CONDUCT.md).