Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes
文献类型： 外文期刊
作者： Yu, Wenjuan 1 ; Luo, Haohui 1 ; Yang, Jinbao 1 ; Zhang, Shengchen 1 ; Jiang, Heling 1 ; Zhao, Xianjia 1 ; Hui, Xingqi 1 ; Sun, Da 1 ; Li, Liang 2 ; Wei, Xiu-qing 2 ; Lonardi, Stefano 3 ; Pan, Weihua 1 ;
作者机构： 1.Chinese Acad Agr Sci, Guangdong Lab Lingnan Modern Agr, Minist Agr & Rural Affairs, Genome Anal Lab,Shenzhen Branch,Agr Genom Inst She, Shenzhen 518120, Peoples R China
2.Fujian Acad Agr Sci, Fruit Res Inst, Fuzhou 350013, Fujian, Peoples R China
3.Univ Calif Riverside, Dept Comp Sci & Engn, Riverside, CA 92521 USA
4.Zhengzhou Univ, Sch Agr Sci, Zhengzhou 450001, Henan, Peoples R China
5.Huazhong Agr Univ, Coll Informat, Wuhan 430070, Peoples R China
期刊名称：GENOME RESEARCH （ 影响因子：6.2； 五年影响因子：8.4 ）
ISSN： 1088-9051
年卷期： 2024 年 34 卷 2 期
页码：
收录情况： SCI
摘要： Pacific Biosciences (PacBio) HiFi sequencing technology generates long reads (>10 kbp) with very high accuracy (<0.01% sequencing error). Although several de novo assembly tools are available for HiFi reads, there are no comprehensive studies on the evaluation of these assemblers. We evaluated the performance of 11 de novo HiFi assemblers on (1) real data for three eukaryotic genomes; (2) 34 synthetic data sets with different ploidy, sequencing coverage levels, heterozygosity rates, and sequencing error rates; (3) one real metagenomic data set; and (4) five synthetic metagenomic data sets with different composition abundance and heterozygosity rates. The 11 assemblers were evaluated using quality assessment tool (QUAST) and benchmarking universal single-copy ortholog (BUSCO). We also used several additional criteria, namely, completion rate, single-copy completion rate, duplicated completion rate, average proportion of largest category, average distance difference, quality value, run-time, and memory utilization. Results show that hifiasm and hifiasm-meta should be the first choice for assembling eukaryotic genomes and metagenomes with HiFi data. We performed a comprehensive benchmarking study of commonly used assemblers on complex eukaryotic genomes and metagenomes. Our study will help the research community to choose the most appropriate assembler for their data and identify possible improvements in assembly algorithms.
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