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Versatile genome assembly evaluation with QUAST-LG

Open access
Mikheenko, Alla, Prjibelski, Andrey, Saveliev, Vladislav, Antipov, Dmitry, Gurevich, Alexey·2018·Bioinformatics

Abstract

Motivation: The emergence of high-throughput sequencing technologies revolutionized genomics in early 2000s. The next revolution came with the era of long-read sequencing. These technological advances along with novel computational approaches became the next step towards the automatic pipelines capable to assemble nearly complete mammalian-size genomes. Results: In this manuscript, we demonstrate performance of the state-of-the-art genome assembly software on six eukaryotic datasets sequenced using different technologies. To evaluate the results, we developed QUAST-LG—a tool that compares large genomic de novo assemblies against reference sequences and computes relevant quality metrics. Since genomes generally cannot be reconstructed completely due to complex repeat patterns and low coverage regions, we introduce a concept of upper bound assembly for a given genome and set of reads, and compute theoretical limits on assembly correctness and completeness. Using QUAST-LG, we show how close the assemblies are to the theoretical optimum, and how far this optimum is from the finished reference. Availability and implementation: http://cab.spbu.ru/software/quast-lg Supplementary information: Supplementary data are available at Bioinformatics online.

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Metadata

Authors
Mikheenko, A., Prjibelski, A., Saveliev, V., Antipov, D., & Gurevich, A.
Venue
Bioinformatics
Published
2018-06-27
Volume
34
Issue
13
Pages
i142-i150
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2808352813
Cited by
1,527
References
52
FWCI
23.70
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Versatile genome assembly evaluation with QUAST-LG. https://app.cochat.ai/papers/10.1093/bioinformatics/bty266
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Mikheenko, A., Prjibelski, A., Saveliev, V., Antipov, D., & Gurevich, A. (2018). Versatile genome assembly evaluation with QUAST-LG. Bioinformatics. https://doi.org/10.1093/bioinformatics/bty266

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