Norbert Dojer | Searcharxiv

arXiv2025

From de Bruijn graphs to variation graphs-relationships between pangenome models

Pangenomes serve as a framework for joint analysis of genomes of related organisms. Several pangenome models were proposed, offering different functionalities, applications provided by available tools, their efficiency etc. Among them, two graph-based models are particularly widely used: variation graphs and de Bruijn graphs. In the current paper we propose an axiomatization of the desirable properties of a graph representation of a collection of strings. We show the relationship between variation graphs satisfying these criteria and de Bruijn graphs. This relationship can be used to efficiently build a variation graph representing a given set of genomes, transfer annotations between both models, compare the results of analyzes based on each model etc.

q-bio.GN↗

arXiv2013

MSARC: Multiple Sequence Alignment by Residue Clustering

Progressive methods offer efficient and reasonably good solutions to the multiple sequence alignment problem. However, resulting alignments are biased by guide-trees, especially for relatively distant sequences. We propose MSARC, a new graph-clustering based algorithm that aligns sequence sets without guide-trees. Experiments on the BAliBASE dataset show that MSARC achieves alignment quality similar to best progressive methods and substantially higher than the quality of other non-progressive algorithms. Furthermore, MSARC outperforms all other methods on sequence sets with the similarity structure hardly represented by a phylogenetic tree. Furthermore, MSARC outperforms all other methods on sequence sets whose evolutionary distances are hardly representable by a phylogenetic tree. These datasets are most exposed to the guide-tree bias of alignments. MSARC is available at http://bioputer.mimuw.edu.pl/msarc

q-bio.QM↗