A Verified Workflow for MiRNA-Seq Data Processing and Bioinformatics Analysis Using R

MicroRNAs (miRNAs) are critical post-transcriptional regulators that influence a wide range of physiological and pathological processes. With the advancement of high-throughput sequencing technologies, miRNA-Seq has emerged as a powerful tool for profiling miRNA expression patterns. However, reliable interpretation of such data requires a standardized and reproducible analysis pipeline. Here, we present a verified workflow for miRNA-Seq data processing and bioinformatics analysis using R. This protocol encompasses all essential steps, including raw data preprocessing, quality control, alignment, quantification, normalization, differential expression analysis, target prediction, functional enrichment, and regulatory network construction. Designed for flexibility and transparency, the workflow integrates widely adopted R packages and supports species-specific annotation and modular customization. Additionally, users are guided to conduct downstream biological interpretation by leveraging curated databases and visualization tools such as Cytoscape. This protocol not only supports robust statistical analysis but also enables meaningful insights into miRNA-mRNA interactions and their roles in disease mechanisms. It is particularly well-suited for both novice and experienced researchers conducting miRNA biomarker discovery, disease modeling, or integrative multi-omics studies.