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Pangenome comparison via ED strings.
Esteban Gabory1, Moses Njagi Mwaniki2, Nadia Pisanti2
1Centrum Wiskunde & Informatica, Amsterdam, Netherlands.
We introduce matching statistics for elastic-degenerate (ED) strings to compare pangenomes. This method, using intersection graphs, offers an efficient and effective way to analyze genomic sequence collections.
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Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Elastic-degenerate (ED) strings offer a simplified representation for pangenomes compared to variation or sequence graphs.
- Pangenome analysis requires robust methods for comparing collections of genomic sequences.
Purpose of the Study:
- To define and compute similarity and distance measures for ED strings, serving as pangenome comparison tools.
- To demonstrate the computational efficiency and practical effectiveness of these new measures.
Main Methods:
- Defined matching statistics for two ED strings as similarity measures.
- Utilized the intersection graph of ED strings for efficient computation of these measures.
- Implemented the methods as a software tool for pangenome comparison.
Main Results:
- The intersection graph method for computing similarity/distance measures is up to ten times faster than the classic product automaton construction.
- The matching statistics successfully reproduced a known SARS-CoV-2 clade classification using real-world data.
- The implemented software tool demonstrated efficiency and effectiveness on both synthetic and real datasets.
Conclusions:
- Matching statistics based on intersection graphs provide an efficient and effective approach for pangenome comparison.
- This method is suitable for analyzing genomic variations and classifications, as shown with SARS-CoV-2 data.

