Cui Y, Peng C, Xia Z, Yang C, Guo Y. A survey of
sequence-to-graph mapping algorithms in the pangenome era.
Genome Biol 2025;
26:138. [PMID:
40405275 PMCID:
PMC12096488 DOI:
10.1186/s13059-025-03606-6]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Accepted: 05/06/2025] [Indexed: 05/24/2025] Open
Abstract
A pangenome can reveal the genetic diversity across different individuals simultaneously. It offers a more comprehensive reference for genome analysis compared to a single linear genome that may introduce allele bias. Pangenomes are often represented as genome graphs, making sequence-to-graph mapping a fundamental task for pangenome construction and analysis. Numerous sequence-to-graph mapping algorithms have been developed over the past few years. Here, we provide a review of the advancements in sequence-to-graph mapping algorithms in the pangenome era. We also discuss the challenges and opportunities that arise in the context of pangenome graphs.
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