Evidence map›Paper›PMID 31510940›Full record

ArticleBMC genomics2019

dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies.

Gokhan Yavas, Huixiao Hong, Wenming Xiao

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Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Gokhan YavasBioinformatics Branch, Division of Bioinformatics and Biostatistics, National Center for Toxicological Center, U.S Food and Drug Administration, Jefferson, AR, 72079, USA.
Huixiao HongBioinformatics Branch, Division of Bioinformatics and Biostatistics, National Center for Toxicological Center, U.S Food and Drug Administration, Jefferson, AR, 72079, USA.
Wenming XiaoBioinformatics Branch, Division of Bioinformatics and Biostatistics, National Center for Toxicological Center, U.S Food and Drug Administration, Jefferson, AR, 72079, USA. Wenming.Xiao@fda.hhs.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly.

resultsTo address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies.

conclusionsThe dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

Indexed as

BenchmarkingContig MappingGenomicsSoftwareAssembly quality assessmentde novo genome assemblyMisassemblyNext generation sequencing

Identifiers

PMID31510940
PMCPMC6737619

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.