ONYX: an alignment-free biological sex inference from high-throughput sequencing data

Biological sex inference from genomic data is important in population genomics, conservation biology, and forensic science, yet many existing approaches depend on sequence alignment or species-specific markers and may therefore be limited in their transferability across sex chromosome systems. ONYX is an alignment-free framework for biological sex inference based on sex chromosome-derived k-mer collections. It constructs homogametic- and heterogametic-specific k-mer collections from reference genomes and infers chromosomal sex configuration directly from sequencing reads using a unified heterogametic signal score, $K{R}_{het}$ . The framework was evaluated using human whole-genome sequencing data representing an XY system and chicken whole-genome sequencing data representing a ZW system. In both species, $K{R}_{het}$ clearly distinguished heterogametic from homogametic individuals. Importantly, the same score interpretation was preserved across both systems, with elevated $K{R}_{het}$ values consistently reflecting heterogametic chromosome content despite differences in genome structure and the biological interpretation of sex. This pattern was also observed in an additional validation using Atlantic cod which has limited heterogametic-specific sequences, further supporting the applicability of ONYX as a unified framework applicable across distinct sex chromosome systems. Its alignment-free design provides a simple and computationally efficient approach for scalable and time-sensitive genomic analysis. ONYX is freely available at https://github.com/omics-tools/onyx.