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

Area of Science:

• Bioinformatics
• Genomics
• Molecular Biology

Background:

• MicroRNAs (miRNAs) are key regulators of gene expression impacting health and disease.
• High-throughput sequencing enables miRNA profiling, but requires standardized analysis.
• Existing miRNA-Seq analysis pipelines lack comprehensive standardization.

Purpose of the Study:

• To present a verified, reproducible R-based workflow for miRNA-Seq data analysis.
• To facilitate robust interpretation of miRNA expression patterns.
• To support miRNA biomarker discovery and disease mechanism studies.

Main Methods:

• Development of an R workflow for end-to-end miRNA-Seq data processing.
• Integration of established R packages for quality control, alignment, and quantification.
• Inclusion of differential expression analysis, target prediction, and network construction modules.
• Guidance on using curated databases and visualization tools like Cytoscape.

Main Results:

• A flexible and transparent protocol for miRNA-Seq data analysis is established.
• The workflow supports species-specific annotations and modular customization.
• Enables robust statistical analysis and biological interpretation of miRNA functions.
• Facilitates the study of miRNA-mRNA interactions and their role in diseases.

Conclusions:

• The presented R workflow provides a standardized approach for miRNA-Seq data analysis.
• It empowers researchers to gain meaningful biological insights from miRNA expression data.
• This protocol is suitable for various applications, including biomarker discovery and multi-omics studies.