Abstract
Metatranscriptomic data analysis is a complex task due to its sheer volume and the need for sophisticated bioinformatics tools. To address this, we developed the Read-based Total-infectome Taxonomic Analysis Pipeline (RTTAP), an automated pipeline for metatranscriptomic data analysis that eliminates the need for users to manually select databases, tools, or parameters. RTTAP provides a comprehensive solution for "total-infectome" analysis, enabling simultaneous detection of viruses, bacteria, and fungi. Additionally, RTTAP delivers detailed functional profiling of antibiotic resistance genes (ARGs) and high-resolution viral strain analysis, offering researchers a powerful tool for advanced metatranscriptomic studies. The pipeline's performance was validated using both simulated and real clinical metatranscriptomic datasets, demonstrating high accuracy in taxonomic classification and relative abundance estimation.