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Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams.

作者信息

Yang Mei, Chen Tong, Liu Yong-Xin, Huang Luqi

机构信息

Institute of Traditional Chinese Medicine Tianjin University of Traditional Chinese Medicine Tianjin China.

State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, National Resource Center for Chinese Materia Medica China Academy of Chinese Medical Sciences Beijing China.

出版信息

Imeta. 2024 Apr 11;3(3):e184. doi: 10.1002/imt2.184. eCollection 2024 Jun.


DOI:10.1002/imt2.184
PMID:38898979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11183158/
Abstract

Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step-by-step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user-friendly tool for the in-depth exploration of multiomics data.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/353d/11183158/1fdf9526527f/IMT2-3-e184-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/353d/11183158/af24ad19e0ab/IMT2-3-e184-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/353d/11183158/1fdf9526527f/IMT2-3-e184-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/353d/11183158/af24ad19e0ab/IMT2-3-e184-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/353d/11183158/1fdf9526527f/IMT2-3-e184-g003.jpg

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Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams.

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[2]
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[6]
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[7]
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[9]
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本文引用的文献

[1]
Complex heatmap visualization.

Imeta. 2022-8-1

[2]
ggVennDiagram: Intuitive Venn diagram software extended.

Imeta. 2024-2-14

[3]
Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses.

Imeta. 2024-2-13

[4]
Ontology characterization, enrichment analysis, and similarity calculation-based evaluation of disease-syndrome-formula associations by applying SoFDA.

Imeta. 2023-1-10

[5]
Microbiota-related metabolites fueling the understanding of ischemic heart disease.

Imeta. 2023-2-26

[6]
EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research.

Imeta. 2023-1-27

[7]
Applying multi-omics toward tumor microbiome research.

Imeta. 2023-1-9

[8]
VeloPro: A pipeline integrating Ribo-seq and AlphaFold deciphers association patterns between translation velocity and protein structure features.

Imeta. 2023-11-19

[9]
Gut microbiota composition in the sympatric and diet-sharing and shaped largely by community assembly processes rather than regional species pool.

Imeta. 2022-10-13

[10]
Metabolite profiling of human-originated Lachnospiraceae at the strain level.

Imeta. 2022-10-13

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