Efficient dynamic variation graphs
Jordan M Eizenga1,2, Adam M Novak1,2, Emily Kobayashi1,3
1Genomics Institute, Santa Cruz, CA 95064, USA.
Motivation:
Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic datasets can be challenging to work at. These challenges have impeded progress in this field.
Results:
Here, we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage are up to an order of magnitude better than the prior graph implementation in the VG toolkit, which has now transitioned to using libbdsg's implementations.
Availability And Implementation:
libhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg.
Related Concept Videos
Dynamic Equilibrium
Velocity and Position by Graphical Method
Variability: Analysis
The range is a simple measure of variability, indicating the difference between the highest and...
Graphs of Functions
Time-Series Graph
Variation
When independent and dependent variables are plotted on a scatter plot, the slope of a line is a value that describes the rate of change between the two...


