4.7 Review

Venn diagrams in bioinformatics

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 5, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbab108

关键词

Venn diagrams; visualization; generator; application

资金

  1. National Natural Science Foundation of China [31871330]
  2. Scientific Research Starting Foundation of Southwest University [SWU118103]
  3. Fundamental Research Funds for the Central Universities [XDJK2019TJ003]
  4. Chongqing Municipal Training Program of Innovation and Entrepreneurship for Undergraduates [S201910635003]

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In this review, various Venn diagram generators and application tools are compared based on their ability to generate high-quality diagrams, handle maximum datasets, input and output formats, and picture beautification parameters. The functional characteristics of popular tools are also briefly described.
Venn diagrams are widely used tools for graphical depiction of the unions, intersections and distinctions among multiple datasets, and a large number of programs have been developed to generate Venn diagrams for applications in various research areas. However, a comprehensive review comparing these tools has not been previously performed. In this review, we collect Venn diagram generators (i.e. tools for visualizing the relationships of input lists within a Venn diagram) and Venn diagram application tools (i.e. tools for analyzing the relationships between biological data and visualizing them in a Venn diagram) to compare their functional capacity as follows: ability to generate high-quality diagrams; maximum datasets handled by each program; input data formats; output diagram styles and image output formats. We also evaluate the picture beautification parameters of the Venn diagram generators in terms of the graphical layout and briefly describe the functional characteristics of the most popular Venn diagram application tools. Finally, we discuss the challenges in improving Venn diagram application tools and provide a perspective on Venn diagram applications in bioinformatics. Our aim is to assist users in selecting suitable tools for analyzing and visualizing user-defined datasets.

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