InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams

BackgroundSet comparisons permeate a large number of data analysis workflows, in particular workflows in biological sciences. Venn diagrams are frequently employed for such analysis but current tools are limited.ResultsWe have developed InteractiVenn, a more flexible tool for interacting with Venn diagrams including up to six sets. It offers a clean interface for Venn diagram construction and enables analysis of set unions while preserving the shape of the diagram. Set unions are useful to reveal differences and similarities among sets and may be guided in our tool by a tree or by a list of set unions. The tool also allows obtaining subsets’ elements, saving and loading sets for further analyses, and exporting the diagram in vector and image formats. InteractiVenn has been used to analyze two biological datasets, but it may serve set analysis in a broad range of domains.ConclusionsInteractiVenn allows set unions in Venn diagrams to be explored thoroughly, by consequence extending the ability to analyze combinations of sets with additional observations, yielded by novel interactions between joined sets. InteractiVenn is freely available online at: www.interactivenn.net.

[1]  Age K Smilde,et al.  A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics* , 2012, Molecular & Cellular Proteomics.

[2]  Stuart Maudsley,et al.  VENNTURE–A Novel Venn Diagram Investigational Tool for Multiple Pharmacological Dataset Analysis , 2012, PloS one.

[3]  R. Tibshirani,et al.  Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  W. Alkema,et al.  BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams , 2008, BMC Genomics.

[5]  Jun Tian,et al.  A Gene Selection Method for Cancer Classification , 2012, Comput. Math. Methods Medicine.

[6]  Stuart Maudsley,et al.  Correction: VENNTURE–A Novel Venn Diagram Investigational Tool for Multiple Pharmacological Dataset Analysis , 2012, PLoS ONE.

[7]  Hisashi Narimatsu,et al.  Toolboxes for a standardised and systematic study of glycans , 2014, BMC Bioinformatics.

[8]  Irina Kalatskaya,et al.  Identification of Differentially Expressed Proteins in Direct Expressed Prostatic Secretions of Men with Organ-confined Versus Extracapsular Prostate Cancer* , 2012, Molecular & Cellular Proteomics.

[9]  Connie R. Jimenez,et al.  On the beta-binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics , 2010, Bioinform..

[10]  Manuel A. R. Ferreira,et al.  Genome-Wide Association Studies of Asthma in Population-Based Cohorts Confirm Known and Suggested Loci and Identify an Additional Association near HLA , 2012, PloS one.

[11]  Saravanaraj N. Ayyampalayam,et al.  The banana (Musa acuminata) genome and the evolution of monocotyledonous plants , 2012, Nature.

[12]  R. Poppi,et al.  Integrative analysis to select cancer candidate biomarkers to targeted validation , 2015, Oncotarget.

[13]  Youping Deng,et al.  GeneVenn - A web application for comparing gene lists using Venn diagrams , 2007, Bioinformation.

[14]  Hans A. Kestler,et al.  Generalized Venn diagrams: a new method of visualizing complex genetic set relations , 2005, Bioinform..

[15]  Jason Weston,et al.  Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.

[16]  Philippe Bardou,et al.  jvenn: an interactive Venn diagram viewer , 2014, BMC Bioinformatics.