Comparing assembly strategies for third-generation sequencing technologies across different genomes
The recent advent of long-read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), has led to substantial accuracy and computational cost improvements. However, de novo whole-genome assembly still presents significant challenges related to the computat...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/395093 |
| Acceso en línea: | https://hdl.handle.net/2117/395093 https://dx.doi.org/10.1016/j.ygeno.2023.110700 |
| Access Level: | acceso abierto |
| Palabra clave: | Genomics Sequence alignment (Bioinformatics) Genome assembly Hybrid assembly HiFi ONT PacBio Genòmica Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| Sumario: | The recent advent of long-read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), has led to substantial accuracy and computational cost improvements. However, de novo whole-genome assembly still presents significant challenges related to the computational cost and the quality of the results. Accordingly, sequencing accuracy and throughput continue to improve, and many tools are constantly emerging. Therefore, selecting the correct sequencing platform, the proper sequencing depth and the assembly tools are necessary to perform high-quality assembly. This paper evaluates the primary assembly reconstruction from recent hybrid and non-hybrid pipelines on different genomes. We find that using PacBio high-fidelity long-read (HiFi) plays an essential role in haplotype construction with respect to ONT reads. However, we observe a substantial improvement in the correctness of the assembly from high-fidelity ONT datasets and combining it with HiFi or short-reads. |
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