Evaluation of the taxonomic classification tools and visualizers for metagenomic analysis using the Oxford nanopore sequence database.

Abstract

Microbial metagenomic identification is generally attributed to the specificity and type of the bioinformatic tools, including classifiers and visualizers. In this study, the performance of two major classifiers, Centrifuge and Kraken2, and two visualizers (Recentrifuge and Krona) has been thoroughly investigated for their efficiency in the identification of the microorganisms using the Whole-Genome Sequence (WGS) database and four targeted databases including NCBI, Silva, Greengenes, and Ribosomal Database Project (RDP). Two standard DNA metagenomic library replicates, Zymo and Zymo-1, were used as quality control. Results showed that Centrifuge gave a higher percentage of Pseudomonas aeruginosa, Escherichia coli, and Salmonella enterica identification than Kraken2. Compared to Recentrifuge, Kraken2 was more accurate in identifying Staphylococcus aureus, Listeria monocytogenes, Bacillus subtilis, and Cryptococcus neoformans. The results of the rest of the detected microorganisms were generally consistent with the two classifiers. Regarding visualizers, both Recentrifuge and Krona provided similar results regarding the abundance of each microbial species regardless of the classifier used. The differences in results between the two mentioned classifiers may be attributed to the specific algorithms each method uses and the sequencing depth. Centrifuge uses a read mapping approach, while Kraken2 uses a k-mer-based system to classify the sequencing reads into taxonomic groups. In conclusion, both Centrifuge and Kraken2 are effective tools for microbial classification. However, the choice of classifier can influence the accuracy of microbial classification and, therefore, should be made carefully, depending on the desired application, even when the same reference database is used.