Impact of database choice and confidence score on the performance of taxonomic classification using Kraken2.

ABSTRACT: Accurate taxonomic classification is essential to understanding microbial diversity and function through metagenomic sequencing. However, this task is complicated by the vast variety of microbial genomes and the computational limitations of bioinformatics tools. The aim of this study was to evaluate the impact of reference database selection and confidence score (CS) settings on the performance of Kraken2, a widely used k-mer-based metagenomic classifier. In this study, we generated simulated metagenomic datasets to systematically evaluate how the choice of reference databases, from the compact Minikraken v1 to the expansive nt- and GTDB r202, and different CS (from 0 to 1.0) affect the key performance metrics of Kraken2. These metrics include classification rate, precision, recall, F1 sco

SUBMITTER: Liu Y 

PROVIDER: S-EPMC11624175 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature