kMermaid: Ultrafast functional classification of microbial reads

Abstract

ABSTRACTShotgun metagenomic sequencing can determine both taxonomic and functional content of microbiomes. However, current functional classification methods for metagenomic reads require substantial computational resources and yield ambiguous classifications, limiting downstream quantitative analyses. Existingk-mer based methods to classify microbial sequences into species-level groups have immensely improved taxonomic classification, but this concept has not been extended to functional classification. Here we introducekMermaid, for classifying metagenomic reads into functional clusters of proteins. Using proteink-mers,kMermaid allows for highly accurate and ultrafast functional classification, with a fixed memory usage, and can easily be employed on a typical computer.