MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics
文献类型： 外文期刊
作者： Bai, Defeng 1 ; Ma, Chuang 1 ; Xun, Jiani 1 ; Luo, Hao 1 ; Yang, Haifei 1 ; Lyu, Hujie 1 ; Zhu, Zhihao 5 ; Gai, Anran 1 ; Yousuf, Salsabeel 1 ; Peng, Kai 7 ; Xu, Shanshan 8 ; Gao, Yunyun 1 ; Wang, Yao 1 ; Liu, Yong-Xin 1 ;
作者机构： 1.Chinese Acad Agr Sci, Agr Genom Inst Shenzhen, Genome Anal Lab, Minist Agr & Rural Affairs, Shenzhen 518120, Peoples R China
2.Anhui Agr Univ, Sch Hort, Hefei, Peoples R China
3.Qingdao Agr Univ, Coll Life Sci, Qingdao, Peoples R China
4.Hong Kong Polytech Univ, Dept Food Sci & Nutr, Hong Kong, Peoples R China
5.Guangdong Med Univ, Marine Biomed Res Inst, Coll Basic Med, Zhanjiang Key Lab Human Microecol & Clin Translat, Zhanjiang, Peoples R China
6.Zhengzhou Univ, Sch Agr Sci, Zhengzhou, Peoples R China
7.Yangzhou Univ, Coll Vet Med, Jiangsu Coinnovat Ctr Prevent & Control Important, Yangzhou, Peoples R China
8.Hefei Univ Technol, Sch Food & Biol Engn, Hefei, Peoples R China
9.Beijing Forestry Univ, Sch Ecol & Nat Conservat, Beijing, Peoples R China
关键词： bioinformatics; interpretation; microbiome; multi-omics; visualization
期刊名称：IMETA （ 影响因子：33.2； 五年影响因子：33.2 ）
ISSN： 2770-5986
年卷期： 2025 年 4 卷 1 期
页码：
收录情况： SCI
摘要： 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 (). 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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