GenGraph: a python module for the simple generation and manipulation of genome graphs.
Background: As sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies. Results: We present the GenGraph toolkit, a tool that uses existing multiple sequence alignment tools to create genome graphs. It is written in Python, one of the most popular coding languages for the biological sciences, and creates the genome graphs as Python NetworkX graph objects. The conceptual model is highly intuitive, and as much as possible represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects. We outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script. Conclusion: GenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model in a widely used coding language. It is publicly available on Github (https://github.com/jambler24/GenGraph).See it on Scoop.it, via Viruses, Immunology & Bioinformatics from Virology.uvic.ca
GenGraph: a python module for the simple generation and manipulation of genome graphs.
Source: Viral Bioinformatics
