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<p>Graph based pangenomes approaches represent a highly effective framework for clustering and comparative analysis of genomes across different subspecies. Traditionally, generating a complete pangenome involves the use of multiple subpackages, understanding of optimization in the light of time and memory complexity and a firm grasp on Linux based command line programming. To address and transform the multi-step command line process into a user-friendly approach, a software package was designed to integrate and automate all the steps involved − (1) genome annotation, (2) gene completeness statistics, (3) gene family cluster simplification and (4) genome-to-gene mapping. The designed package boasts improved memory footprint and runtime optimizations by implementing parallelization of processes, achieving a speedup of 2.53x when implemented on a test set of 150 genomes. To demonstrate its functionality and validate its accuracy, the tool was used as a test case to generate a pangenome and analyze genomes of <i>Geobacillus</i> species. The genomes chosen in the final pangenome were curated based on the metrics of CheckM Completeness and BUSCO (Benchmarking Universal Single-Copy Orthologs) scores. Annotation of the genomes was performed by PROKKA and then clustered by PPanGGOLiN. Post-processing modules for Gene Ontology and UniProt analysis are also included. The entire software package was designed in a modular fashion - to allow users the option to switch out modules for either ones designed by themselves or ones tailored to their requirements.</p>

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An optimized and integrated robust tool for pangenome generation

  • 期刊论文

  • 发表日期：

    2026年3月21日

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  • Sherwyn Braganza,
  • Tanvi Govil,
  • Dipayan Samanta,
  • Randy Hoover,
  • David Salem,
  • Rajesh Sani

摘要

Graph based pangenomes approaches represent a highly effective framework for clustering and comparative analysis of genomes across different subspecies. Traditionally, generating a complete pangenome involves the use of multiple subpackages, understanding of optimization in the light of time and memory complexity and a firm grasp on Linux based command line programming. To address and transform the multi-step command line process into a user-friendly approach, a software package was designed to integrate and automate all the steps involved − (1) genome annotation, (2) gene completeness statistics, (3) gene family cluster simplification and (4) genome-to-gene mapping. The designed package boasts improved memory footprint and runtime optimizations by implementing parallelization of processes, achieving a speedup of 2.53x when implemented on a test set of 150 genomes. To demonstrate its functionality and validate its accuracy, the tool was used as a test case to generate a pangenome and analyze genomes of Geobacillus species. The genomes chosen in the final pangenome were curated based on the metrics of CheckM Completeness and BUSCO (Benchmarking Universal Single-Copy Orthologs) scores. Annotation of the genomes was performed by PROKKA and then clustered by PPanGGOLiN. Post-processing modules for Gene Ontology and UniProt analysis are also included. The entire software package was designed in a modular fashion - to allow users the option to switch out modules for either ones designed by themselves or ones tailored to their requirements.