MIRit: an integrative R framework for the identification of impaired miRNA-mRNA regulatory networks in complex diseases

MicroRNAs (miRNAs) are critical regulators of gene expression, implicated in nearly all cellular processes and frequently associated with pathological development. Given their broad functional significance, systematic and accurate characterization of miRNA dysregulation is essential to uncover the molecular underpinnings of disease. While high-throughput technologies such as microarrays and miRNA-Seq enable the quantification of small RNA transcripts, deciphering their functional roles in disease mechanisms remains a major challenge. This is partly due to the lack of standardized, integrative frameworks for miRNA-mRNA analysis and the widespread reliance on outdated or inappropriate methodologies, which often yield poorly reproducible results and limited insights into miRNA regulatory networks. Moreover, the absence of statistical models tailored for non-sample-matched datasets significantly hampers the exploitation of many existing miRNA datasets, further restricting their biological interpretability. To address these limitations, we present MIRit, an open-source, comprehensive R framework designed to support rigorous, state-of-the-art integrative analyses of miRNA and mRNA data. MIRit guides users through all critical steps, including differential expression analysis of miRNAs and mRNAs, and identification of miRNA-target pairs using ensemble-based prediction methods combined with validated interactions. It further integrates miRNA and mRNA expression profiles using statistically robust techniques such as partial correlation analysis, rotation gene set tests, and one-sided association tests. Beyond integration, MIRit offers a suite of tools for exploring dysregulated miRNA networks, including the identification of disease-associated variants affecting miRNA expression and the assessment of the functional impact of miRNA dysregulation.