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
{"title":"MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics","authors":"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","doi":"10.1002/imt2.70002","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"4 1","pages":""},"PeriodicalIF":23.7000,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.70002","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"iMeta","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/imt2.70002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.