Gene set enrichment analysis is frequently used to interpretat clinical and other omics data, but methods for identifying enrichment trends in multidimensional data are lacking. We developed an R package for multi-dimensional gene set enrichment analysis called mitch. mitch uses a rank-MANOVA based statistical approach to identify sets of genes that exhibit joint enrichment across multiple contrasts. The package’s unique visualisation features enable the exploration of enrichments in two or more dimensions. In this presentation we provide an overview of a mitch workflow and present case studies spanning multi-contrast RNA expression profiling, integrative multi-omics, tool benchmarking and single cell RNA sequencing. Using simulated data we show mitch has similar accuracy to state of the art tools for unidimensional enrichment analysis, and high overall accuracy in identifying multidimensional enrichments. In conclusion, mitch is a versatile tool for rapidly identifying and visualising gene set enrichments in multidimensional omics data.