纳米孔测序
顺序装配
杂交基因组组装
基因组学
基因组
DNA测序
生物
计算生物学
选择(遗传算法)
数据科学
领域(数学)
计算机科学
人工智能
遗传学
基因
基因表达
转录组
数学
纯数学
作者
Elena Espinosa,Rocío Bautista,Rafael Larrosa Jiménez,Óscar Plata
出处
期刊:Genomics
[Elsevier]
日期:2024-04-11
卷期号:116 (3): 110842-110842
被引量:6
标识
DOI:10.1016/j.ygeno.2024.110842
摘要
The recent advent of long read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), have led to substantial improvements in accuracy and computational cost in sequencing genomes. However, de novo whole-genome assembly still presents significant challenges related to the quality of the results. Pursuing de novo whole-genome assembly remains a formidable challenge, underscored by intricate considerations surrounding computational demands and result quality. As sequencing accuracy and throughput steadily advance, a continuous stream of innovative assembly tools floods the field. Navigating this dynamic landscape necessitates a reasonable choice of sequencing platform, depth, and assembly tools to orchestrate high-quality genome reconstructions. This comprehensive review delves into the intricate interplay between cutting-edge long read sequencing technologies, assembly methodologies, and the ever-evolving field of genomics. With a focus on addressing the pivotal challenges and harnessing the opportunities presented by these advancements, we provide an in-depth exploration of the crucial factors influencing the selection of optimal strategies for achieving robust and insightful genome assemblies.
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