Work

YACHT: Software for an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample

Year: 2026

Type: article

Abstract: Identifying genomes in metagenomic samples can be complicated by taxonomic profiling tools that lack uncertainty quantification and rely on incomplete reference databases.YACHT (Yes/No Answers to Community membership via Hypothesis Testing) introduces a 𝑘-mer sketching based statistical framework that incorporates average nucleotide identity (ANI) and coverage, the portion of 𝑘-mers observed for a microbe's genome detected in a sample, to detect genetic similarity between reference and sample genomes using binomial hypothesis testing on exclusive 𝑘-mers to confidently determine genome presence/absence (Koslicki et al., 2024).This paper describes the software implementation of this methodology as a command-line tool that detects low-abundant species while controlling the false-negative rate, making it applicable to functional profiling, metatranscriptomics, and clinical microbiome analysis despite incomplete genomes and variable coverage.YACHT is developed with C++ and Python and depends on sourmash (Irber et al., 2024) for 𝑘-mer extraction and management.

Source: The Journal of Open Source Software

DOI: 10.21105/joss.09066