Leviathan: A fast, memory-efficient, and scalable taxonomic and pathway profiler for (pan)genome-resolved...

Functional profiling of meta-omics is essential for understanding microbial communities, yet support for custom genome-resolved reference databases is limited. We introduce Leviathan for integrated taxonomic and functional profiling at both genome and pangenome resolution. Leviathan combines Sylph for ultrafast alignment-free taxonomic profiling with Salmon for pseudo-alignment-based read quantification in DNA-space against (pan)genome-resolved gene catalogs, producing dual metrics per (pan)genome: pathway abundance and graph-based pathway coverage. Benchmarking alignment backends on synthetic metagenomes, we show that DNA-space pseudo-alignments retain competitive (pan)genome-level classification performance compared to traditional alignment, reducing computational runtime and memory requirements, while translated searches in protein-space lose classification resolution from ambiguous mapping events. Leviathan's utility is demonstrated through two case studies: a marine plastisphere metagenomics dataset analyzing metabolic shifts between early and mature biofilm communities and a dental caries metatranscriptomics dataset where coexpression network analysis identified organism-specific transcriptional patterns diagnostic of health and disease states. Leviathan is available at https://github.com/jolespin/leviathan.