Abstract

BackgroundNew sequencing technologies have made it possible to explore genetic diversity at higher resolution in microbial populations. However, our understanding evolutionary relationships, and comparison of closely and distantly related bacterial genomes from these massive datasets remains a formidable challenge. Numerous clustering algorithms that group genomic data based on homology have been developed, but new tools are still required to analyse the resultant orthologous maps to understand functional genetic similarities and their phyletic patterns (patterns of presence of absence of genes).FindingsBacterial Makeup eXplorer (BMX) implements an algorithm that swiftly and efficiently facilitates the determination of the number of orthologs in prokaryotic genomes employing a reference free approach, which may be further exploited to transfer of gene annotations. BMX is able to integrate orthologous maps of highly diverse prokaryotic genomes therefore making it possible to perform robust and scalable, multi-platform, high quality annotation transfer and gene-by-gene composition assessment method. In addition results are presented in the form of publication quality figures.ConclusionsBMX allows extensive data analysis of orthologous map databases to understand underlying biological relationships. Furthermore, BMX is portable across different platforms and can be installed easily. In summary, BMX allows higher resolution analysis of genomes from diverse bacterial populationsElectronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1017-z) contains supplementary material, which is available to authorized users.

Highlights

  • New sequencing technologies have made it possible to explore genetic diversity at higher resolution in microbial populations

  • Bacterial Makeup eXplorer (BMX) is portable across different platforms and can be installed

  • We describe Bacterial Makeup eXplorer (BMX), a highly efficient, stand alone tool that can be used to and effectively compute the size and composition of the genes common to all strain genomes, within each gene cluster under study from OrthoMCL [16] generated orthologous gene maps

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Summary

Conclusions

BMX allows extensive data analysis of orthologous map databases to understand underlying biological relationships. BMX is portable across different platforms and can be installed . BMX allows higher resolution analysis of genomes from diverse bacterial populations

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