RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• RNA-sequencing (RNA-Seq) analysis is crucial for understanding transcriptomes.
• Existing RNA-Seq tools often lack integration, requiring significant computational resources and expertise.
• A need exists for comprehensive, user-friendly RNA-Seq analysis pipelines in a pure R environment.

Purpose of the Study:

• To develop an open-source R/Bioconductor package, RNASeqR, for automated, end-to-end RNA-Seq analysis.
• To provide researchers with fundamental tabular and graphical results for biological interpretation.
• To integrate existing R and command-line software tools into a cohesive pipeline.

Main Methods:

• Developed the RNASeqR package in R/Bioconductor.
• Integrated popular R and command-line software tools for RNA-Seq analysis.
• Implemented a six-step automated analysis workflow.

Main Results:

• RNASeqR offers a fast, light-weight, and easy-to-run RNA-Seq analysis pipeline.
• The package provides comprehensive visualization and essential results for biological interpretation.
• It supports background execution and integrates diverse software tools without environment predefinition.

Conclusions:

• RNASeqR addresses the need for an integrated and accessible RNA-Seq analysis tool.
• The package facilitates efficient transcriptomic data analysis for researchers on Linux and macOS.
• RNASeqR enhances biological interpretation by providing fundamental end-to-end results.