Pan-genome de Bruijn graph using the bidirectional FM-index.
BMC Bioinformatics
; 24(1): 400, 2023 Oct 26.
Article
em En
| MEDLINE
| ID: mdl-37884897
ABSTRACT
BACKGROUND:
Pan-genome graphs are gaining importance in the field of bioinformatics as data structures to represent and jointly analyze multiple genomes. Compacted de Bruijn graphs are inherently suited for this purpose, as their graph topology naturally reveals similarity and divergence within the pan-genome. Most state-of-the-art pan-genome graphs are represented explicitly in terms of nodes and edges. Recently, an alternative, implicit graph representation was proposed that builds directly upon the unidirectional FM-index. As such, a memory-efficient graph data structure is obtained that inherits the FM-index' backward search functionality. However, this representation suffers from a number of shortcomings in terms of functionality and algorithmic performance.RESULTS:
We present a data structure for a pan-genome, compacted de Bruijn graph that aims to address these shortcomings. It is built on the bidirectional FM-index, extending the ability of its unidirectional counterpart to navigate and search the graph in both directions. All basic graph navigation steps can be performed in constant time. Based on these features, we implement subgraph visualization as well as lossless approximate pattern matching to the graph using search schemes. We demonstrate that we can retrieve all occurrences corresponding to a read within a certain edit distance in a very efficient manner. Through a case study, we show the potential of exploiting the information embedded in the graph's topology through visualization and sequence alignment.CONCLUSIONS:
We propose a memory-efficient representation of the pan-genome graph that supports subgraph visualization and lossless approximate pattern matching of reads against the graph using search schemes. The C++ source code of our software, called Nexus, is available at https//github.com/biointec/nexus under AGPL-3.0 license.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Genoma
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article