Molecular Biology and Evolution · 2021 · 72 citations · 21 references
Life SciencesBioinformaticsMicrobiologyGenome AssemblyGenomicsPhylogeneticsDe Novo Genome AssemblyGenome SequencingMetagenome AssemblyMetagenomic Data Quality ControlPhylogenomic AnalysisSequence AssemblyAssembly Completeness EvaluationGenome Completeness AssessmentGenome ReconstructionGenome Reconstruction From MetagenomesMetagenome-assembled GenomesPhylogenetic AnnotationPhylogenetic PlacementSingle-copy Ortholog Identification
Evaluating genomic and metagenomic data quality is essential for accurate genome assembly and downstream analyses. The study introduces new functionalities and major improvements to BUSCO, renewing and expanding its datasets in line with OrthoDB v10. BUSCO estimates genome completeness and redundancy from universal single‑copy orthologs, now automatically selects the appropriate dataset through phylogenetic placement, supports metagenome‑assembled genomes, offers a new workflow that improves efficiency on large eukaryotic genomes, and uniquely assesses both eukaryotic and prokaryotic species across assemblies, bins, transcriptomes, and gene sets.
Abstract Methods for evaluating the quality of genomic and metagenomic data are essential to aid genome assembly procedures and to correctly interpret the results of subsequent analyses. BUSCO estimates the completeness and redundancy of processed genomic data based on universal single-copy orthologs. Here, we present new functionalities and major improvements of the BUSCO software, as well as the renewal and expansion of the underlying data sets in sync with the OrthoDB v10 release. Among the major novelties, BUSCO now enables phylogenetic placement of the input sequence to automatically select the most appropriate BUSCO data set for the assessment, allowing the analysis of metagenome-assembled genomes of unknown origin. A newly introduced genome workflow increases the efficiency and runtimes especially on large eukaryotic genomes. BUSCO is the only tool capable of assessing both eukaryotic and prokaryotic species, and can be applied to various data types, from genome assemblies and metagenomic bins, to transcriptomes and gene sets.
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