Benchmarking metagenomic tools for taxonomic profiling in epidemiological applications

Abstract

The study of microbiomes plays a crucial role in understanding health and disease, yet accurately identifying microbial species from metagenomic data remains challenging due to the limitations of taxonomic annotation tools. This master's thesis project focuses on the comparison of various metagenomic taxonomic profiling tools to determine their efficacy on metagenomic sequenced samples. This study is important for example for epidemiological applications, as an accurate understanding of bacterial distribution and diversity can help in the understanding of species involved in disease. The tools have been compared using a mock dataset and related real-world dataset from a publicly available study. The results of these comparisons may provide valuable insights for researchers working on characterizing microbiome composition, potentially advancing both diagnostic and therapeutic applications.