Manually weighted taxonomy classifiers improve species-specific rumen microbiome analysis compared to unweighted or average weighted taxonomy classifiers.

ABSTRACT: Previous research has demonstrated that applying taxonomic weights to shotgun metagenomic data can improve species identification in 16S rRNA gene-based microbiome analysis. However, such an approach does not allow for accurate analysis of samples collected from less studied habitats, such as rumen. In the present study, we developed a method to incorporate taxonomic weights based on relative abundance of species identified from shotgun sequencing and amplicon sequencing data derived from rumen. Using this weighting method, we evaluated latest versions of five prominent databases-SILVA, Greengenes2 (GG2), RDP, NCBI RefSeq, and GTDB-against the BLAST 16S rRNA database, assessing classification counts, fully classified ratios (proportion of ASVs classified to a known genus and species), and

SUBMITTER: Kang R 

PROVIDER: S-EPMC12586449 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature