Identifying and quantifying isoforms from accurate full-length transcriptome sequencing reads with Mandalorion

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Accurate identification and quantification of full-length transcriptome sequencing reads are crucial for understanding gene expression and function.
• Existing tools face challenges in precision and recall, especially without genome annotation.

Purpose of the Study:

• To introduce and benchmark Mandalorion v4.1 for analyzing full-length transcriptome sequencing data.
• To evaluate its performance in isoform identification and quantification compared to previous versions and in challenging scenarios.

Main Methods:

• Processing of both real and simulated full-length transcriptome sequencing data.
• Benchmarking Mandalorion v4.1 against established performance metrics for identification and quantification.

Main Results:

• Mandalorion v4.1 demonstrates very high precision in isoform identification, maintaining high recall even without genome annotation.
• Isoform read counts quantified by Mandalorion show a strong correlation with simulated read counts.
• Identified isoforms closely represent the input full-length transcriptome sequencing data.

Conclusions:

• Mandalorion v4.1 is a highly effective tool for full-length transcriptome analysis, offering superior performance in isoform identification and quantification.
• Its ability to function without genome annotation significantly enhances its utility in diverse genomic research settings.