ArticleiMetaOmics2025
RTTAP: Empowering metatranscriptomic data analysis with a read-based total-infectome taxonomic solution.
Article in iMetaOmics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
5 authors.
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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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.