Gretl overview. (A) Genome graph construction workflow: genome graph properties are influenced by various factors, including parameter selection, sample curation, and methodology, all of which impact the layout and structure of the resulting genome graph. For evaluation purposes, multiple graphs can be simultaneously generated and compared to identify an optimal representation for a specific task. The selected graph can then be analyzed with gretl. (B) Visualization of gretl output: left, graphs can be clustered based on multiple statistics, grouping similar species or construction parameters (shown here, with normalized values). Right, scatter plot depicting two selected statistics across various graphs, facilitating comparisons between different species. (C) In-depth analysis of a selected genome graph (example from yeast): left, path-centric sliding window analysis of the Saccharomyces cerevisiae genome graph, highlighting regions of high similarity. Right, pan-genomic analysis of the genome graph. Sequences found only in a single sample are separated and each block represents one path of the graph.