miARma-Seq: a comprehensive tool for miRNA, mRNA and circRNA analysis

Area of Science:

• Bioinformatics
• Transcriptomics
• Computational Biology

Background:

• Large-scale RNA sequencing (RNAseq) generates high-resolution transcriptomic data, but its analysis remains challenging.
• Existing tools for microRNA (miRNA) and messenger RNA (mRNA) expression profiling have limitations in scope and data handling.
• The need for integrated, flexible, and accessible analysis solutions for complex RNAseq data is evident.

Purpose of the Study:

• To develop and present miARma-Seq, a versatile bioinformatics pipeline for comprehensive RNAseq data analysis.
• To enable the identification and analysis of miRNA, mRNA, and circular RNA (circRNA) expression profiles.
• To provide a user-friendly, installable tool that integrates established software for differential expression, target prediction, and functional analysis.

Main Methods:

• Development of the miARma-Seq pipeline as a stand-alone, multithreaded tool.
• Integration of well-established bioinformatics software for RNAseq analysis.
• Application of the pipeline to validated datasets for performance assessment.

Main Results:

• miARma-Seq successfully identifies miRNAs, mRNAs, and circRNAs across different organisms.
• The pipeline facilitates differential expression analysis, miRNA-mRNA target prediction, and functional enrichment.
• Demonstrated efficiency in analyzing large sample cohorts due to its multithreaded design.

Conclusions:

• miARma-Seq offers a flexible and accessible solution for complex transcriptomic data analysis.
• The pipeline overcomes limitations of existing tools, supporting diverse organisms and analyses.
• miARma-Seq is readily available to the research community, enhancing the study of gene expression profiles.