ONYX: Alignment-Free Biological Sex Inference from Sequencing Data

An alignment-free framework for biological sex inference from genomic sequencing data, developed by Koji Ishiya. It uses sex chromosome-derived k-mer collections and a unified heterogametic signal score, KRhet, evaluated on human, chicken, and Atlantic cod whole-genome sequencing data. The framework is designed for scalable and time-sensitive genomic analysis and was last updated on 2026-05-28.

Use Cases

• Infer biological sex in population genomics studies based on the described heterogametic signal score KRhet.
• Apply a unified sex inference framework across different sex chromosome systems (XY, ZW) based on the alignment-free k-mer method.
• Perform scalable and computationally efficient sex inference from high-throughput sequencing data based on the described framework design.

Strengths

• Framework validated on multiple species (human, chicken, Atlantic cod) representing different sex chromosome systems.
• Alignment-free design provides computational efficiency for scalable analysis, as mentioned in the description.
• Freely available under a CC-BY-4.0 license from a public GitHub repository.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is a 830.3 KB PDF document, which suggests limited scope and may not contain the raw underlying data.

Provenance

Source

figshare

Collection Method

Likely contains methodological description and evaluation results for the ONYX framework.

Freshness

Last updated 2026-05-28 06:20:52; freshness should be verified.