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.

Authors

Institutions

Publication Details

Journal
iMeta
Published
2025-02-01
DOI
https://doi.org/10.1002/imt2.70002
Citations
12
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
9.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Kai Peng, Defeng Bai, Yunyun Gao, Salsabeel Yousuf et al.
12 citations
iMeta
Metabolomics and Mass Spectrometry Studies
9.67
article

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

Kai Peng, Defeng Bai, Yunyun Gao, Salsabeel Yousuf, Yao Wang, Shanshan Xu, Yongxin Liu, Jiani Xun, Zhihao Zhu, Hao Luo, Hujie Lyu, Chuang Ma, Haifei Yang, Anran Gai
article en
12 citations

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.

iMetaVol. 4(1)
Anhui Agricultural University (CN), Hong Kong Polytechnic University (HK), Qingdao Agricultural University (CN), Hefei University of Technology (CN), Guangdong Medical College (CN), Beijing Forestry University (CN), Zhengzhou University (CN), Agricultural Genomics Institute at Shenzhen (CN), Chinese Academy of Agricultural Sciences (CN), Ministry of Agriculture and Rural Affairs (CN), Yangzhou University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Chinese Academy of Agricultural Sciences, Agricultural Science and Technology Innovation Program
Openalex Percentile: Top 2%
Metabolomics and Mass Spectrometry Studies
9.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.