数字农科院2.0

NextDenovo: an efficient error correction and accurate assembly tool for noisy long reads

文献类型: 外文期刊

作者: Jiang Hu;Zhuo Wang;Zongyi Sun;Benxia Hu;Adeola Oluwakemi Ayoola;Fan Liang;Jingjing Li;José R. Sandoval;David N. Cooper;Kai Ye;Jue Ruan;Chuan Le Xiao;Depeng Wang;Dong Dong Wu;Sheng Wang

作者机构:

关键词: Error-correction;Genome assembly;Human genomes;Long reads;Segmental duplication

期刊名称: Genome Biology

ISSN: 1474-7596

年卷期: 2024 年 25 卷 1 期

页码:

收录情况: SCIE(2024版)

摘要: Long-read sequencing data, particularly those derived from the Oxford Nanopore sequencing platform, tend to exhibit high error rates. Here, we present NextDenovo, an efficient error correction and assembly tool for noisy long reads, which achieves a high level of accuracy in genome assembly. We apply NextDenovo to assemble 35 diverse human genomes from around the world using Nanopore long-read data. These genomes allow us to identify the landscape of segmental duplication and gene copy number variation in modern human populations. The use of NextDenovo should pave the way for population-scale long-read assembly using Nanopore long-read data.

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