Abstract
VennPainter is a program for depicting unique and shared sets of genes lists and generating Venn diagrams, by using the Qt C++ framework. The software produces Classic Venn, Edwards’ Venn and Nested Venn diagrams and allows for eight sets in a graph mode and 31 sets in data processing mode only. In comparison, previous programs produce Classic Venn and Edwards’ Venn diagrams and allow for a maximum of six sets. The software incorporates user-friendly features and works in Windows, Linux and Mac OS. Its graphical interface does not require a user to have programing skills. Users can modify diagram content for up to eight datasets because of the Scalable Vector Graphics output. VennPainter can provide output results in vertical, horizontal and matrix formats, which facilitates sharing datasets as required for further identification of candidate genes. Users can obtain gene lists from shared sets by clicking the numbers on the diagram. Thus, VennPainter is an easy-to-use, highly efficient, cross-platform and powerful program that provides a more comprehensive tool for identifying candidate genes and visualizing the relationships among genes or gene families in comparative analysis.
Highlights
In comparative genomics, the visualization of results can help viewers discover correlations and trends in large datasets [1,2,3,4]
Larger datasets often present an insurmountable challenge to deciphering and drawing Venn diagrams of shared relationships manually. This complexity might explain the dearth of applications [34,35,36,37]. To rectify this limitation and address Venn-based demands, we report the development of VennPainter, a program that introduces a new nested Venn layout
To demonstrate the functions of VennPainter, we use it to depict shared gene sets in the goldfish x common carp hybrid system using eight annotated gene lists generated from RNA-seq data (S4 Fig) [37]
Summary
The visualization of results can help viewers discover correlations and trends in large datasets [1,2,3,4]. The Classic Venn diagram deciphers no more than four sets. Edwards’ and Nested methods might generate Venn diagram for an infinite number sets, but the partition of sets among multiple datasets might have complex associations because distinct open regions increase exponentially with the increase in set-number. VennTure [32] can generate six-sets Venn diagrams with a graphic user interface (GUI), yet it consumes large amounts of memory and has low computational efficiency.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
