Assessing genome assembly quality using the LTR Assembly Index (LAI)

Ou, Shujun; Chen, Jinfeng; Jiang, Ning

doi:10.1093/nar/gky730

Cited by 455 publications

(657 citation statements)

References 42 publications

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“…The long terminal repeat (LTR) index for the assembly (Ou et al, 2018) is 6.65, with 1.42% of intact LTRs 20.66% of total LTRs. This LTR index indicates a high-quality draft assembly comparable to apple v1.0 or cacao v1.0.…”

Section: Genome Assemblymentioning

confidence: 99%

An Improved Chromosome-scale Genome Assembly and Population Genetics resource forPopulus tremula

Schiffthaler

Robinson

Lü

et al. 2019

Preprint

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The genome assembly of the European aspen Populus tremula proved difficult for a short-read based strategy due to high genomic variation. As a consequence, the fragmented sequence is impeding studies that benefit from highly contiguous data, particularly genome-wide association studies (GWAS) and comparative genomics. Here we present an updated assembly based on long-read sequences, optical mapping and genetic mapping. This assembly - henceforth referred to as Potra V2 - is assembled into 19 contiguous chromosomes which provides a powerful tool for future association studies. The genome sequence and any feature files are available from the PopGenIE resource.

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Section: Genome Assemblymentioning

confidence: 99%

An Improved Chromosome-scale Genome Assembly and Population Genetics resource forPopulus tremula

Schiffthaler

Robinson

Lü

et al. 2019

Preprint

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“…Conserved benchmarking universal single-copy orthologs (BUSCO) (13) or core eukaryotic genes mapping approach (CEGMA) (14) were used to assess genome completeness simply based on evaluating the coding or gene space. LTR Assembly Index (LAI) that indicates the assembly quality of LTR (Long Terminal Repeats) retrotransposons was designed to evaluate assembly continuity, extending assembly quality assessment to repetitive regions (15).…”

Section: Introductionmentioning

confidence: 99%

Estimating Assembly Base Errors Using K-mer Abundance Difference (KAD) Between Short Reads and Genome Assembled Sequences

Lin

et al. 2020

Preprint

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Genome sequences provide genomic maps with a single-base resolution for exploring genetic contents. Sequencing technologies, particularly long reads, have revolutionized genome assemblies for producing highly continuous genome sequences. However, current long-read sequencing technologies generate inaccurate reads that contain many errors. Some errors are retained in assembled sequences, which are typically not completely corrected by using either long reads or more accurate short reads. The issue commonly exists but few tools are dedicated for computing error rates or determining error locations. In this study, we developed a novel approach, referred to as K-mer Abundance Difference (KAD), to compare the inferred copy number of each k-mer indicated by short reads and the observed copy number in the assembly. Simple KAD metrics enable to classify k-mers into categories that reflect the quality of the assembly. Specifically, the KAD method can be used to identify base errors and estimate the overall error rate. In addition, sequence insertion and deletion as well as sequence redundancy can also be detected. Therefore, KAD is valuable for quality evaluation of genome assemblies and, potentially, provides a diagnostic tool to aid in precise error correction. KAD software has been developed to facilitate public uses.

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“…LAI is particularly useful for assessing plant genome assemblies, which are often largely comprised of repeats. Recently, dramatic increases in the completeness of repetitive portions of plant genomes have been achieved due to improvements in longread data [9].…”

Section: Introductionmentioning

confidence: 99%

GenomeQC: A quality assessment tool for genome assemblies and gene structure annotations

Manchanda

Portwood²,

Woodhouse³

et al. 2019

Preprint

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BackgroundGenome assemblies are foundational for understanding the biology of a species. They provide a physical framework for mapping additional sequences, thereby enabling characterization of, for example, genomic diversity and differences in gene expression across individuals and tissue types. Quality metrics for genome assemblies gauge both the completeness and contiguity of an assembly and help provide confidence in downstream biological insights. To compare quality across multiple assemblies, a set of common metrics are typically calculated and then compared to one or more gold standard reference genomes. While several tools exist for calculating individual metrics, applications providing comprehensive evaluations of multiple assembly features are, perhaps surprisingly, lacking. Here, we describe a new toolkit that integrates multiple metrics to characterize both assembly and gene annotation quality in a way that enables comparison across multiple assemblies and assembly types. FindingsOur application, named GenomeQC, is an easy-to-use and interactive web framework that integrates various quantitative measures to characterize genome assemblies and annotations. GenomeQC provides researchers with a comprehensive summary of these statistics and allows for benchmarking against gold standard reference assemblies.

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Assessing genome assembly quality using the LTR Assembly Index (LAI)

Cited by 455 publications

References 42 publications

An Improved Chromosome-scale Genome Assembly and Population Genetics resource forPopulus tremula

An Improved Chromosome-scale Genome Assembly and Population Genetics resource forPopulus tremula

Estimating Assembly Base Errors Using K-mer Abundance Difference (KAD) Between Short Reads and Genome Assembled Sequences

GenomeQC: A quality assessment tool for genome assemblies and gene structure annotations

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