Identifying and removing haplotypic duplication in primary genome assemblies

Author:

Guan Dengfeng12,McCarthy Shane A2ORCID,Wood Jonathan3,Howe Kerstin3ORCID,Wang Yadong1,Durbin Richard23ORCID

Affiliation:

1. Department of Computer Science and Technology, Center for Bioinformatics, Harbin Institute of Technology, Harbin 150001, China

2. Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK

3. Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK

Abstract

Abstract Motivation Rapid development in long-read sequencing and scaffolding technologies is accelerating the production of reference-quality assemblies for large eukaryotic genomes. However, haplotype divergence in regions of high heterozygosity often results in assemblers creating two copies rather than one copy of a region, leading to breaks in contiguity and compromising downstream steps such as gene annotation. Several tools have been developed to resolve this problem. However, they either focus only on removing contained duplicate regions, also known as haplotigs, or fail to use all the relevant information and hence make errors. Results Here we present a novel tool, purge_dups, that uses sequence similarity and read depth to automatically identify and remove both haplotigs and heterozygous overlaps. In comparison with current tools, we demonstrate that purge_dups can reduce heterozygous duplication and increase assembly continuity while maintaining completeness of the primary assembly. Moreover, purge_dups is fully automatic and can easily be integrated into assembly pipelines. Availability and implementation The source code is written in C and is available at https://github.com/dfguan/purge_dups. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Key Research and Development Program of China

Wellcome Trust

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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