Integrating sequence composition information into microbial diversity analyses with k-mer frequency counting.

ABSTRACT: k-mer frequency information in biological sequences is used for a wide range of applications, including taxonomy classification, sequence similarity estimation, and supervised learning. However, in spite of its widespread utility, k-mer counting has been largely neglected for diversity estimation. This work examines the application of k-mer counting for alpha and beta diversity as well as supervised classification from microbiome marker-gene sequencing data sets (16S rRNA gene and full-length fungal internal transcribed spacer [ITS] sequences). Results demonstrate a close correspondence with phylogenetically aware diversity metrics, and advantages for using k-mer-based metrics for measuring microbial biodiversity in microbiome sequencing surveys. k-mer counting appears to be a suitable and

SUBMITTER: Bokulich NA 

PROVIDER: S-EPMC11915819 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature