Link to HAL – hal-04831168
2024
MUSET is a novel set of utilities designed to efficiently construct abundance unitig matrices from sequencing data. Unitig matrices extend the concept of k-mer matrices, which are gaining popularity for sequence-phenotype association studies, by merging overlapping k-mers that unambiguously belong to the same sequence. MUSET addresses the limitations of current software by integrating k-mer counting and unitig extraction to generate unitig matrices containing abundance values, as opposed to only presence-absence in previous tools. These matrices preserve variations between samples while reducing disk space and reducing the number of rows in comparison to k-mer matrices. We evaluated MUSET’s performance using datasets derived from a 618-GB collection of ancient oral sequencing samples, producing a filtered unitig matrix that records abundances in less than 10 hours and 20 GB memory. As a comprehensive pipeline for generating these matrices, MUSET will facilitate the extraction of biologically significant sequences, making it a valuable contribution to downstream sequencing data analyses such as genome-wide (or metagenome-wide) association studies.