gINTomics visualizer, a powerful shiny app for multiomics data integration visualization.

Author(s): Angelo Velle,Francesco Patanè,Stefania Pirrotta,Chiara Romualdi

Affiliation(s): University of Padova



Large datasets containing different omics are increasingly available in public databases. However, capturing all the information contained in these data is a major challenge. To solve this need, we developed gINTomics, an easy-to-use R package for omics data integration. However, the interpretation of the integration results is a fundamental step of the analysis, that’s why we decided to include in gINTomics a powerful shiny app for an easy and visually appealing interpretation of the statistical models. gINTomics is designed to detect the association between the expression of a target and of its regulators while taking into account their genomics modifications such as Copy Number Variations and methylation. When the number of regulators is too high, a random forest model will automatically select only the most important regulators. Moreover, the gINTomics visualizer allows the visualization of the results for all the integrations performed. It is divided into four sections: Genomic Integration for the results regarding copy number variations and methylation; Transcription Integration for those regarding transcriptional networks (Transcription Factors and miRNA); Class Comparison for highlighting the results only for genes that are differentially expressed among classes defined by the user; Complete Integration for a comprehensive table with all the available results and a Circos plot for the visualization of different integrations. Our package provides solid multi-omics integration models coupled with a powerful shiny app for results visualization.