基因组
工作流程
微生物群
管道(软件)
适应性
计算机科学
寄主(生物学)
数据科学
生物
生物信息学
生态学
数据库
基因
生物化学
程序设计语言
作者
Defeng Bai,Tong Chen,Jiani Xun,Chuang Ma,Hao Luo,Haifei Yang,Chen Cao,Xiaofeng Cao,Jianzhou Cui,Yuan‐Ping Deng,Zhaochao Deng,Weimin Dong,Wenxue Dong,Juan Du,Qunkai Fang,Fang Wei,Yue Fang,Fangcheng Fu,Min Fu,Yingxun Fu
出处
期刊:iMeta
[Wiley]
日期:2025-02-01
卷期号:4 (1): e70001-e70001
被引量:24
摘要
Abstract Shotgun metagenomics has become a pivotal technology in microbiome research, enabling in‐depth analysis of microbial communities at both the high‐resolution taxonomic and functional levels. This approach provides valuable insights of microbial diversity, interactions, and their roles in health and disease. However, the complexity of data processing and the need for reproducibility pose significant challenges to researchers. To address these challenges, we developed EasyMetagenome, a user‐friendly pipeline that supports multiple analysis methods, including quality control and host removal, read‐based, assembly‐based, and binning, along with advanced genome analysis. The pipeline also features customizable settings, comprehensive data visualizations, and detailed parameter explanations, ensuring its adaptability across a wide range of data scenarios. Looking forward, we aim to refine the pipeline by addressing host contamination issues, optimizing workflows for third‐generation sequencing data, and integrating emerging technologies like deep learning and network analysis, to further enhance microbiome insights and data accuracy. EasyMetageonome is freely available at https://github.com/YongxinLiu/EasyMetagenome .
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