HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• RNA editing is a crucial co-/post-transcriptional mechanism that diversifies the transcriptome and proteome.
• Current automated RNA editing detection from RNA-seq data is computationally demanding, limiting genome-wide analysis.
• Existing tools struggle with large datasets, hindering comprehensive characterization of RNA editing.

Purpose of the Study:

• To introduce HPC-REDItools, an enhanced computational tool for RNA editing event discovery.
• To enable accurate and efficient analysis of RNA editing across large-scale RNA sequencing data repositories.
• To overcome the limitations of previous tools in handling big data for RNA editing studies.

Main Methods:

• Development of HPC-REDItools, an upgraded version of REDItools.
• Implementation of a Message Passing Interface (MPI)-based parallelization strategy.
• Optimization for high-performance computing (HPC) environments to process large datasets.

Main Results:

• HPC-REDItools demonstrates dramatically increased speed compared to the previous REDItools version.
• The tool enables big-data analysis for RNA editing event discovery.
• Performance scales almost linearly with the number of available computing cores, showcasing high efficiency.

Conclusions:

• HPC-REDItools significantly enhances the capability for genome-wide RNA editing characterization.
• The tool's speed and scalability facilitate big-data analysis in RNA editing research.
• This advancement supports a more comprehensive understanding of RNA editing's role in biological diversity.