| Literature DB >> 33526886 |
Haoyu Cheng1,2, Gregory T Concepcion3, Xiaowen Feng1,2, Haowen Zhang4, Heng Li5,6.
Abstract
Haplotype-resolved de novo assembly is the ultimate solution to the study of sequence variations in a genome. However, existing algorithms either collapse heterozygous alleles into one consensus copy or fail to cleanly separate the haplotypes to produce high-quality phased assemblies. Here we describe hifiasm, a de novo assembler that takes advantage of long high-fidelity sequence reads to faithfully represent the haplotype information in a phased assembly graph. Unlike other graph-based assemblers that only aim to maintain the contiguity of one haplotype, hifiasm strives to preserve the contiguity of all haplotypes. This feature enables the development of a graph trio binning algorithm that greatly advances over standard trio binning. On three human and five nonhuman datasets, including California redwood with a ~30-Gb hexaploid genome, we show that hifiasm frequently delivers better assemblies than existing tools and consistently outperforms others on haplotype-resolved assembly.Entities:
Mesh:
Year: 2021 PMID: 33526886 PMCID: PMC7961889 DOI: 10.1038/s41592-020-01056-5
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547