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

It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub () and Gitee (). EasyAmplicon is a user-friendly, cross-platform, and community-supported pipeline for amplicon data analysis. It has most of the modules for data processing and visualization in microbiome research. The pipeline is maintained and updated regularly. We encourage users to contribute appropriate code.Highlightsimage EasyAmplicon is a user-friendly, cross-platform, and community-supported pipeline for amplicon data analysis.It has most of the modules for data processing and visualization in microbiome research.The pipeline is maintained and updated regularly, and we encourage users to contribute appropriate code.