Motivation: Compared to traditional haploid reference genomes, graph genomes are an efficient and compact data structure for storing multiple genomic sequences, for storing polymorphisms or for mapping sequencing reads with greater sensitivity. Further, graphs are well-studied computer science objects that can be efficiently analyzed. However, their adoption in genomic research is slow, in part because of the cognitive difficulty in interpreting graphs.
Results: We present an intuitive graphical representation for graph genomes that re-uses well-honed techniques developed to display public transport networks, and demonstrate it as a web tool.
Availability and implementation: Code: https://github.com/vgteam/sequenceTubeMap.
Demonstration: https://vgteam.github.io/sequenceTubeMap/.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2019. Published by Oxford University Press.