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PMID: 33526886 Published · ppublish English Journal Article Research Support, N.I.H., Extramural

Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm.

Nature methods ·Vol. 18 ·No. 2 ·2021-00-00 ·Pages 170-175

Cheng H, Concepcion GT, Feng X, Zhang H, Li H

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.

MeSH Terms
Algorithms Genome Haplotypes Sequence Analysis, DNA/methods
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Cheng Haoyu ORCID
Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. | Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Concepcion Gregory T ORCID
Pacific Biosciences, Menlo Park, CA, USA.
Feng Xiaowen ORCID
Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. | Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Zhang Haowen
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Li Heng ORCID
Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA. [email protected]. | Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. [email protected].
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Article Info
Journal
Nature methods
Abbr.
Nat Methods
ISSN
1548-7105
Published
2021-00-00
Epub
2021-00-01
Pages
170-175
Language
English
Region
United States
NLM ID
101215604
PMCID
PMC7961889
Subset
IM
Grants
NHGRI NIH HHS · U01 HG010961 · United States
NHGRI NIH HHS · U01 HG010971 · United States
NHGRI NIH HHS · R01 HG010040 · United States
NHGRI NIH HHS · U41 HG010972 · United States
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