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Comparative analysis of HiSeq3000 and BGISEQ-500 sequencing platform over whole genome sequencing metagenomics data.
Kumar, Animesh; Robertsen, Espen M; Willassen, Nils P; Fu, Juan; Hjerde, Erik.
Afiliación
  • Kumar A; Center for Bioinformatics, Department of Chemistry, UiT The Arctic University of Norway, Tromsø, 9037, Norway.
  • Robertsen EM; Center for Bioinformatics, Department of Chemistry, UiT The Arctic University of Norway, Tromsø, 9037, Norway.
  • Willassen NP; Center for Bioinformatics, Department of Chemistry, UiT The Arctic University of Norway, Tromsø, 9037, Norway.
  • Fu J; Faculty of Biosciences, Department of Livestock and Aquaculture Science, Norwegian University of Life Sciences, Ås 1433, Norway.
  • Hjerde E; Center for Bioinformatics, Department of Chemistry, UiT The Arctic University of Norway, Tromsø, 9037, Norway.
Genomics Inform ; 21(4): e49, 2023 Dec.
Article en En | MEDLINE | ID: mdl-38224716
ABSTRACT
Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Genomics Inform Año: 2023 Tipo del documento: Article País de afiliación: Noruega

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Genomics Inform Año: 2023 Tipo del documento: Article País de afiliación: Noruega