GenGraph

GenGraph generates and manipulates genome graphs to represent collections of genomes as unified graph structures for comparative genomics and variation analysis in organisms such as Mycobacterium tuberculosis.

Key Features:

• Python-based implementation: Implemented in Python for programmatic generation and manipulation of genome graphs.
• Genome graph generation and manipulation: Constructs and edits graph representations that encode sequences and their relationships across multiple genomes.
• Integration with multiple sequence alignment tools: Leverages existing multiple sequence alignment (MSA) tools to inform graph construction.
• Graph-based representation of genome collections: Represents collections of genomes as unified genome graphs rather than single reference sequences.
• Conceptual model reflecting biological relationships: Encodes biological relationships between genomes within the graph structure.
• Compatibility with existing formats and tools: Supports widely used file formats and enables export/import and visualization in Cytoscape, R, and JavaScript environments.
• Addresses single-reference limitations: Provides an alternative to single-reference genomes to capture variation across related or differently annotated genomes.

Scientific Applications:

• Variant discovery and representation: Enables comprehensive representation and analysis of genetic variation across multiple genomes within a single graph.
• Comparative genomics and evolutionary analysis: Supports inference of evolutionary relationships and comparative analyses from graph topology and sequence paths.
• Pathogen diversity and epidemiology: Facilitates analysis of strain diversity, adaptation, and variation in pathogens such as Mycobacterium tuberculosis.
• Annotation-aware analyses for high-variability organisms: Allows integration of detailed annotations across genomes to study genomic adaptations in highly variable species.

Methodology:

GenGraph uses multiple sequence alignment tools to generate genome graphs that capture biological differences between genomes.