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• W4367315258 abstract "Recovering high-quality metagenome-assembled genomes (HQ-MAGs) is critical for exploring microbial compositions and microbe-phenotype associations. However, multiple sequencing platforms and computational tools for this purpose may confuse researchers and thus call for extensive evaluation. Here, we systematically evaluated a total of 40 combinations of popular computational tools and sequencing platforms (i.e. strategies), involving eight assemblers, eight metagenomic binners and four sequencing technologies, including short-, long-read and metaHiC sequencing. We identified the best tools for the individual tasks (e.g. the assembly and binning) and combinations (e.g. generating more HQ-MAGs) depending on the availability of the sequencing data. We found that the combination of the hybrid assemblies and metaHiC-based binning performed best, followed by the hybrid and long-read assemblies. More importantly, both long-read and metaHiC sequencings link more mobile elements and antibiotic resistance genes to bacterial hosts and improve the quality of public human gut reference genomes with 32% (34/105) HQ-MAGs that were either of better quality than those in the Unified Human Gastrointestinal Genome catalog version 2 or novel." @default.
• W4367315258 created "2023-04-29" @default.
• W4367315258 creator A5003760095 @default.
• W4367315258 creator A5013097653 @default.
• W4367315258 creator A5021764064 @default.
• W4367315258 creator A5046944569 @default.
• W4367315258 creator A5049435754 @default.
• W4367315258 creator A5064247976 @default.
• W4367315258 date "2023-04-27" @default.
• W4367315258 modified "2023-10-12" @default.
• W4367315258 title "A survey on computational strategies for genome-resolved gut metagenomics" @default.
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• W4367315258 doi "https://doi.org/10.1093/bib/bbad162" @default.
• W4367315258 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37114640" @default.
• W4367315258 hasPublicationYear "2023" @default.
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