gINTomics is an R package for Multi-Omics data integration and visualization. gINTomics is designed to detect the association between the expression of a target and of its regulators, taking into account also their genomics modifications such as Copy Number Variations (CNV) and methylation. For RNA sequencing data, the counts will be fitted using a negative binomial model, while in the case of microarray or other types of data, a linear model will be applied. In some cases the number of regulators for a given target could be very high, in order to handle this eventuality, we provide a random forest selection that will automatically keep only the most important regulators. All the models are gene-specific, so each gene/miRNA will have its own model with its covariates. The package will automatically download information about TF-target couples (OmnipathR), miRNA-target couples (OmnipathR) and TF-miRNA couples (TransmiR). The couples will be used to define the covariates used in the integration models.