The　haplotype　assembly　problem　has　been　proven　to　be　complex.　Heuristic　algorithms　are　the　main　methods　that　are　used　to　solve　the　problem.　These　algorithms　perform　well　when　the　SNP　fragments　are　error-free,　but　they　are　less　accurate　when　the　error　rate　increases.　The　complex　relationships　caused　by　fragment　errors　present　a　major　barrier　to　assembling　accurate　haplotypes.　Therefore,　modeling　the　complex　relationships　is　the　key　to　solve　the　problem.　In　this　study,　we　model　the　haplotype　assembly　problem　using　hypergraph　partitioning　formulations　and　propose　a　novel　method　termed　HGHap　(Hypergraph-based　Haplotype　assembly　method).　HGHap　approaches　the　haplotype　assembly　problem　in　two　phases.　In　the　first　phase,　a　hypergraph　is　constructed　in　which　each　vertex　corresponds　to　a　fragment　and　vertices　are　multiply　connected　to　form　hyperedges.　In　the　second　phase,　a　hypergraph　partitioning　algorithm　is　employed　to　obtain　two　groups　of　fragments　to　construct　the　haplotypes.　The　hyperedges　capture　higher-order　relationships　among　fragments　that　facilitate　the　subsequent　partitioning.　Our　results　demonstrate　that　the　method　performs　better　than　other　methods　in　most　cases,　especially　in　cases　with　a　high　error　rate.　(C)　2014　Elsevier　Ltd.　All　rights　reserved.