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pmid:40434911

HSDSnake: a user-friendly SnakeMake pipeline for analysis of duplicate genes in eukaryotic genomes.

Xi Zhang · Yining Hu · David Roy Smith · Zhenyu Cheng · John M Archibald

Bioinformatics (Oxford, England) · 2025 doi:10.1093/bioinformatics/btaf325

Paper

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Experiment

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HSDSnake: a user-friendly SnakeMake pipeline for analysis of duplicate genes in eukaryotic genomes.
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10.1093/bioinformatics/btaf325
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Xi Zhang
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Yining Hu
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David Roy Smith
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Zhenyu Cheng
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John M Archibald
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year
2025
abstract
SUMMARY: Gene duplication is a well-known driver of molecular evolution-it acts as a source of genetic novelty, thereby providing the raw substrate for organismal adaption. However, detecting different types of gene duplicates and comparing them in sequence datasets can be difficult. Existing tools can identify and classify gene duplicates that have arisen by various processes, but have limitations; for example, some do not have a user-friendly workflow and can include many intermediate steps requiring manual adjustments of parameters and/or are not maintained for the benefit of research community members. Here, we have developed HSDSnake, a user-friendly SnakeMake pipeline that can detect and classify gene duplications into five categories: dispersed, proximal, tandem, transposed, and whole genome. It also curates and evaluates the highly similar gene duplicates (HSDs) in each gene duplication category with reliance on both sequence similarity and conserved domains. Lastly, the detected gene duplicates can be visualized within a KEGG functional pathway framework and the substitution rates (Ka, Ks, and their Ka/Ks ratio) can be analyzed for all the duplicate gene pairs. We demonstrate HSDSnake's capabilities by analyzing two reference genomes directly downloaded from NCBI and provide detailed instructions for each step. AVAILABILITY AND IMPLEMENTATION: The HSDSnake pipeline uses SnakeMake and Conda to run and install dependencies. The distribution version is available online at GitHub: https://github.com/zx0223winner/HSDSnake and the archived version at Zenodo is https://doi.org/10.5281/zenodo.15521945.
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