MicrobiomeStatPlots:用于元组学和生物信息学的微生物组统计图库

IF 23.7 Q1 MICROBIOLOGY
iMeta Pub Date : 2025-02-17 DOI:10.1002/imt2.70002
Defeng Bai, Chuang Ma, Jiani Xun, Hao Luo, Haifei Yang, Hujie Lyu, Zhihao Zhu, Anran Gai, Salsabeel Yousuf, Kai Peng, Shanshan Xu, Yunyun Gao, Yao Wang, Yong-Xin Liu
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引用次数: 0

摘要

微生物组研究的快速发展产生了前所未有的多组学数据,在数据分析和可视化方面提出了挑战。为了解决这些问题,我们提出了MicrobiomeStatPlots,这是一个全面的平台,为微生物组数据分析和可视化提供了简化的、可重复的工具。该平台将基本的生物信息学工作流程与多组学管道集成,并提供82种不同的可视化案例来解释微生物组数据集。通过结合基本教程和先进的基于r的可视化策略,MicrobiomeStatPlots增强了研究人员的可访问性和可用性。用户可以自定义图,为平台的扩展做出贡献,并在GitHub (https://github.com/YongxinLiu/MicrobiomeStatPlot)上自由访问丰富的生物信息学知识。未来的计划包括扩展对代谢组学、病毒组学和超转录组学的支持,以及将可视化工具无缝集成到组学工作流程中。MicrobiomeStatPlots填补了微生物组数据分析和可视化方面的空白,为更有效、更有影响力的微生物组研究铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics

MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics

The rapid growth of microbiome research has generated an unprecedented amount of multi-omics data, presenting challenges in data analysis and visualization. To address these issues, we present MicrobiomeStatPlots, a comprehensive platform offering streamlined, reproducible tools for microbiome data analysis and visualization. This platform integrates essential bioinformatics workflows with multi-omics pipelines and provides 82 distinct visualization cases for interpreting microbiome datasets. By incorporating basic tutorials and advanced R-based visualization strategies, MicrobiomeStatPlots enhances accessibility and usability for researchers. Users can customize plots, contribute to the platform's expansion, and access a wealth of bioinformatics knowledge freely on GitHub (https://github.com/YongxinLiu/MicrobiomeStatPlot). Future plans include extending support for metabolomics, viromics, and metatranscriptomics, along with seamless integration of visualization tools into omics workflows. MicrobiomeStatPlots bridges gaps in microbiome data analysis and visualization, paving the way for more efficient, impactful microbiome research.

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