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ContigExtender
ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data
ID:50749UploaderBioTreasury
2022.01.19
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Abstract
Background: Metagenomics is the study of microbial genomes for pathogen detection and discovery in human clinical, animal, and environmental samples via Next-Generation Sequencing (NGS). Metagenome de novo sequence assembly is a crucial analytical step in which longer contigs, ideally whole chromosomes/genomes, are formed from shorter NGS reads. However, the contigs generated from the de novo assembly are often very fragmented and rarely longer than a few kilo base pairs (kb). Therefore, a time-consuming extension process is routinely performed on the de novo assembled contigs. Results: To facilitate this process, we propose a new tool for metagenome contig extension after de novo assembly. ContigExtender employs a novel recursive extending strategy that explores multiple extending paths to achieve highly accurate longer contigs. We demonstrate that ContigExtender outperforms existing tools in synthetic, animal, and human metagenomics datasets. Conclusions: A novel software tool ContigExtender has been developed to assist and enhance the performance of metagenome de novo assembly. ContigExtender effectively extends contigs from a variety of sources and can be incorporated in most viral metagenomics analysis pipelines for a wide variety of applications, including pathogen detection and viral discovery.
Keywords
De novo assembly; Metagenomics; Next-Gen Sequencing; Pathogen detection; Viral discovery
Publication
ContigExtender: a new approach to improving de novo sequence assembly for viral metagenomics data
Zachary Deng,Eric DelwartBMC Bioinformatics2021
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Sequencing
Read mapping
Sequence assembly
Genes & Genomes
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