Detecting high-scoring local alignments in pangenome graphs

Author:

Schulz Tizian123ORCID,Wittler Roland12ORCID,Rahmann Sven4ORCID,Hach Faraz56ORCID,Stoye Jens12ORCID

Affiliation:

1. Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld 33615, Germany

2. Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Bielefeld University, Bielefeld 33615, Germany

3. Graduate School ‘Digital Infrastructure for the Life Sciences’ (DILS), Bielefeld University, Bielefeld 33615, Germany

4. Genome Informatics, Institute of Human Genetics, University Hospital Essen, University of Duisburg-Essen, Essen 45122, Germany

5. Vancouver Prostate Centre, Vancouver, BC V6H 3Z6, Canada

6. Department of Urologic Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada

Abstract

Abstract Motivation Increasing amounts of individual genomes sequenced per species motivate the usage of pangenomic approaches. Pangenomes may be represented as graphical structures, e.g. compacted colored de Bruijn graphs, which offer a low memory usage and facilitate reference-free sequence comparisons. While sequence-to-graph mapping to graphical pangenomes has been studied for some time, no local alignment search tool in the vein of BLAST has been proposed yet. Results We present a new heuristic method to find maximum scoring local alignments of a DNA query sequence to a pangenome represented as a compacted colored de Bruijn graph. Our approach additionally allows a comparison of similarity among sequences within the pangenome. We show that local alignment scores follow an exponential-tail distribution similar to BLAST scores, and we discuss how to estimate its parameters to separate local alignments representing sequence homology from spurious findings. An implementation of our method is presented, and its performance and usability are shown. Our approach scales sublinearly in running time and memory usage with respect to the number of genomes under consideration. This is an advantage over classical methods that do not make use of sequence similarity within the pangenome. Availability and implementation Source code and test data are available from https://gitlab.ub.uni-bielefeld.de/gi/plast. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

German Network for Bioinformatics Infrastructure

European Union’s Horizon 2020 research and innovation program

Marie Skłodowska-Curie

DFG

National Science and Engineering Council of Canada

Michael Smith Foundation for Health Research

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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