Pagoo: An Encapsulated and Object-Oriented Framework for Evolutionary Analysis of Bacterial Pangenomes

Abstract

Pangenome analysis is fundamental to explore molecular evolution occurring in bacterial populations. Despite the extensive availability of software for pangenome reconstruction, there is a lack of tools that allow customization of downstream data analysis in a simple and standardized way. To fill this gap, we introduce Pagoo, a new framework that enables straightforward handling of pangenome data. The encapsulated nature of Pagoo allows the storage of complex molecular and phenotypic information using an object-oriented approach that includes built-in methods, allowing the user going back and forward to the data using a single programming environment. Also, this design allows to save any analysis along with the unaltered pangenome data in a single file, making it sharable and reproducible. Pagoo acts as an API between the pangenome data and the user through the R console, providing tools to query, subset, compare, visualize and perform statistical analyses, which can be also used in concert with other microbial genomics packages available in the R ecosystem. As working examples, we used 1,000 Escherichia coli genomes to show that Pagoo is scalable, and a global dataset of Campylobacter fetus genomes to identify evolutionary patterns and genomic markers of host-adaptation in this pathogen. Pagoo represents an integrative and extensible approach to make pangenome analysis simple and reproducible.