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Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams.
Yang, Mei; Chen, Tong; Liu, Yong-Xin; Huang, Luqi.
Afiliação
  • Yang M; Institute of Traditional Chinese Medicine Tianjin University of Traditional Chinese Medicine Tianjin China.
  • Chen T; 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.
  • Liu YX; 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.
  • Huang L; Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China.
Imeta ; 3(3): e184, 2024 Jun.
Article em En | MEDLINE | ID: mdl-38898979
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article