HPC-T-Annotator: an HPC tool for de novo transcriptome assembly annotation.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Transcriptomic data from species lacking a reference genome necessitates de novo transcriptome assembly.
• De novo assembly yields unigenes for homology-based functional annotation, a computationally intensive process.
• Current homology annotation methods present significant computational challenges.

Purpose of the Study:

• To introduce HPC-T-Annotator, a novel tool for efficient de novo transcriptome homology annotation.
• To leverage high-performance computing (HPC) infrastructures for reduced computational burden.
• To provide a user-friendly interface for complex annotation tasks.

Main Methods:

• Development of HPC-T-Annotator, a parallel computing software for transcriptome annotation.
• Web interface for straightforward configuration of annotation parameters.
• Automatic generation and execution of parallel computing software on supercomputers.
• Integration of Python notebooks for post-processing and data visualization.

Main Results:

• HPC-T-Annotator significantly expedites homology-based annotation of de novo transcriptome assemblies.
• Efficient parallelization on HPC infrastructures drastically reduces computational load and execution times.
• The tool enables large-scale transcriptome analysis and comparative projects.

Conclusions:

• HPC-T-Annotator enhances the efficiency and accessibility of de novo transcriptome annotation.
• The intuitive graphical interface makes advanced computational analysis accessible to researchers without IT expertise.
• The software facilitates broader adoption of large-scale transcriptome analysis.