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

Motivation: MicroRNAs (miRNAs) play a central role in controlling gene expression, and their abnormal activity is frequently linked to disease. Despite advancements in transcriptomic technologies, elucidating miRNA-mediated mechanisms remains challenging due to methodological limitations and a lack of standardized frameworks. Results: To overcome these barriers, we developed MIRit, a comprehensive R package designed for the rigorous analysis of miRNA–mRNA interactions. With flexible support for both matched and unmatched datasets, MIRit leverages cutting-edge target identification strategies and applies suitable statistical approaches for each scenario. In this study, we benchmarked the performance of commonly used statistical tests for integrative miRNA analysis and demonstrated the effectiveness of MIRit across three human disease contexts—dilated cardiomyopathy, clear cell renal cell carcinoma, and Alzheimer’s disease—by uncovering functionally relevant miRNA–target disruptions consistent with known disease mechanisms. Through its streamlined pipeline and biologically appropriate methods, MIRit enables more reproducible and accurate insights into the complex landscape of post-transcriptional regulation. Availability and implementation: The tool is fully open-source and freely accessible via Bioconductor, making it readily available to the broader scientific community.