IntroductionAn elastic-degenerate (ED) string is a sequence of sets of strings.It can also be seen as a directed acyclic graph whose edges are labeled by strings.The notion of ED strings was introduced as a simple alternative to variation and sequence graphs for representing a pangenome, that is, a collection of genomic sequences to be analyzed jointly or to be used as a reference.
MethodsIn this study, we define notions of matching statistics of two ED strings as similarity measures Cutting Board Racks between pangenomes and, consequently infer a corresponding distance measure.We then show that both measures can be computed efficiently, in both theory and practice, by employing the intersection graph of two ED strings.ResultsWe also implemented our methods as a software tool for pangenome comparison and evaluated their efficiency and effectiveness using both synthetic and real datasets.
DiscussionAs for efficiency, we compare the runtime of the intersection graph method against the classic product automaton construction showing that the intersection Pentair UltraTemp Parts graph is faster by up to one order of magnitude.For showing effectiveness, we used real SARS-CoV-2 datasets and our matching statistics similarity measure to reproduce a well-established clade classification of SARS-CoV-2, thus demonstrating that the classification obtained by our method is in accordance with the existing one.