Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome - Animal Microbiome

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Investigating the impact of database choice on the accuracy of metagenomic read classification for the rumen microbiome - Animal Microbiome
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Classification rate, classification accuracy and taxonomic read classification are heavily impacted by the choice of reference database used, finds a study published in Animal Microbiome.

Species levels. Each bar represents reads classified by Kraken2, using each reference database as shown along the x-axis. The bars represent the percentage of classified reads at various classification status, as shown in the key. “Truth unknown” refers to the reads that originate from genomes that do not have an assigned family or genus. “Unclassified at any level” refers to reads that were not classified to any taxonomic level.

At the species level, use of both of the RefSeq and the Mini databases classified a similar proportion of reads correctly . However, using the RefSeq database incorrectly classified almost the same proportion , whereas using the Mini database incorrectly classified approximately half that amount . As expected for a smaller database, classification with the Mini database had a higher proportion of reads that were unclassified at any level compared to RefSeq .

Table 2 The frequency of families and genera in the Hungate and RUG datasets, and overlap between the two datasetsThe poor performance of RUGs at this level, as demonstrated in classification accuracy for the RUG database, also impacted the RefRUG database. Use of both reference databases including RUGs resulted in over 35% of reads being incorrectly classified.

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