Haplotype-aware Sequence-to-Graph Alignment

Abstract

AbstractModern pangenome graphs are built using high-quality phased haplotype sequences such that each haplotype sequence corresponds to a path in the graph. Prioritizing the alignment of reads to these paths improves genotyping accuracy (Sirenet al., Science 2021). However, rigorous formulations for sequence-to-graph chaining and alignment do not consider the haplotype paths. As a result, the search space increases combinatorially as more variants are augmented in the graph. This limitation affects the effectiveness of the algorithms. In this paper, we propose novel formulations and provably good algorithms for haplotype-aware pattern matching of sequences to directed acyclic graphs (DAGs). Our work considers both sequence-to-DAG chaining and sequence-to-DAG alignment problems. Drawing inspiration from the commonly used models for genotype imputation, we assume that a query sequence is an imperfect mosaic of the reference haplotypes. Accordingly, our formulations extend previous chaining and alignment formulations by introducing a recombination penalty for a haplotype switch. First, we solve the haplotype-aware sequence-to-DAG alignment inO(|Q| |E||ℋ |) time whereQis the query sequence,Eis the set of edges, and ℋis the set of haplotypes represented in the graph. Second, we prove that an algorithm significantly faster thanO(|Q| |E||ℋ |) is unlikely. Third, we propose a haplotype-aware chaining algorithm that usesO(|ℋ |Nlog |ℋ |N) time, whereNis the count of exact matches. As a proof-of-concept, we implemented the chaining algorithm in the Minichain aligner (https://github.com/at-cg/minichain). Using simulated human major histocompatibility complex (MHC) query sequences and a pangenome graph of 60 publicly available MHC haplotypes, we show that the proposed algorithm offers a much better consistency between the ground-truth recombinations and the recombinations in the output chains when compared to a haplotype-agnostic algorithm.