EasyAmplicon

The Chinese version in (中文版见) README_cn.md

EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research

Version：v1.21

Update：2024/08/05

Pipeline manual and file description

Using RStudio to open the pipeline available in Chinese (pipeline.sh) and English (pipeline_en.sh)

Files Description:

Readme.md # Introduction and install
pipeline.sh # Command-line analysis for Windows and Linux (available in Chinese and English)
pipeline_mac.sh # Command-line analysis for MacOS
result/ # Example result data
result/Diversity.Rmd # Interactive diversity analysis in R and output reproducible report in HTML format

What can we do?

Analysis and visualization of microbiome data, especially for 16S rDNA amplicon;
From raw data into feature tables;
Support 20+ analysis methods and publish-ready visualization;
Finish your project on your laptop in short time (approx 3 hours);
Supporting materials manual and videos in Chinese/English.

Figure 1. The pipeline of EasyAmplicon for analyzing paired-end amplicon sequences.

Figure 2. Examples of publication-quality visualizations.

Figure 3. Supplementary examples of publication-quality visualizations to Figure 2.

Figure 4. Visualizations generated by third-party software using the intermediate files of EasyAmplicon.

Install

Install Dependency

All the software backups can be found in

FTP: Filezilla visiting FTP download.nmdc.cn in anonymous. In the tools directory, you can find all the software and packages in amplicon and different systems supporting such mac, win
Baidu Net Disk：https://pan.baidu.com/s/1Ikd_47HHODOqC3Rcx6eJ6Q?pwd=0315

Please install the dependency software according to your system (Win/Mac/Linux).

R 4.x.x is recommended for running R scripts https://www.r-project.org/. It is also recommended that Rtools be installed for source code packages.
RStudio 2023.xx.x is a integrated development environment for R https://posit.co/download/rstudio-desktop/
STAMP v2.1.3 http://kiwi.cs.dal.ca/Software/STAMP
Git for Windows 2.xx.x (Windows only) http://gitforwindows.org/
R packages quick install

The statistics and visualization may require > 500 R packages. Installation is time-consuming and may also rely on other compilation tools. You can download all needed R packages in https://pan.baidu.com/s/1Ikd_47HHODOqC3Rcx6eJ6Q?pwd=0315 db/win/4.x.zip or db/mac/R4.2_mac_libraryX86_64.zip, then unzip and take the 4.x folder in C:\Users[$UserName]\AppData\Local\R\win-library\

Install EasyAmplicon

Method 1. Visit the GitHub homepage, Code -- Download
EasyAmplicon pipeline (Positive control) https://github.com/YongxinLiu/EasyAmplicon
EasyMicrobiome includes scripts and databases https://github.com/YongxinLiu/EasyMicrobiome

Download the project in C: or D: then unzip (keep the directory name exactly the software name)

Method 2. Download by the mirror site in BaiduNetDisk: https://pan.baidu.com/s/1Ikd_47HHODOqC3Rcx6eJ6Q?pwd=0315 db/soft/EasyAmplicon.tar.gz or EasyMicrobiome.tar.gz
Method 3. git clone https://github.com/YongxinLiu/EasyAmplicon and git clone https://github.com/YongxinLiu/EasyMicrobiome. Note: fatal: unable to access can retry.

Quick Start

Using Windows 10+ as an example:

Open RStudio, and set the terminal as Git Bash (Tools -- Global Options -- Terminal -- New terminals -- Git Bash -- OK)
File -- Open File -- EasyAmplicon folder -- pipeline.sh (windows/linux) or pipeline_mac.sh (mac)
Setup the work directory(wd), and EasyMicrobiome directory(db), then run each line by clicking run in the top right corner

Example dataset

seq/ # raw sequencing in zipped fastq format, backup can download by metadata from GSA https://ngdc.cncb.ac.cn/gsa/
result/ # Example data and figures for standard pipeline, such as alpha, beta, tax
advanced/ # Example of advanced analysis, included data, scripts and output figures

FAQ

Frequently Asked Questions in pipeline.sh

Note: All the .sh script is written in markdown format, using Youdao Note or VSCode for a better reading experience.

Citation

If use this script, please cite:

Yong-Xin Liu, Lei Chen, Tengfei Ma, Xiaofang Li, Maosheng Zheng, Xin Zhou, Liang Chen, Xubo Qian, Jiao Xi, Hongye Lu, Huiluo Cao, Xiaoya Ma, Bian Bian, Pengfan Zhang, Jiqiu Wu, Ren-You Gan, Baolei Jia, Linyang Sun, Zhicheng Ju, Yunyun Gao, Tao Wen, Tong Chen. 2023. EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research. iMeta 2: e83. https://doi.org/10.1002/imt2.83

YongxinLiu / EasyAmplicon

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