GAGE: A critical evaluation of genome assemblies and assembly algorithms

McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Genome Research (Impact Factor: 14.63). 12/2011; 22(3):557-67. DOI: 10.1101/gr.131383.111
Source: PubMed


New sequencing technology has dramatically altered the landscape of whole-genome sequencing, allowing scientists to initiate numerous projects to decode the genomes of previously unsequenced organisms. The lowest-cost technology can generate deep coverage of most species, including mammals, in just a few days. The sequence data generated by one of these projects consist of millions or billions of short DNA sequences (reads) that range from 50 to 150 nt in length. These sequences must then be assembled de novo before most genome analyses can begin. Unfortunately, genome assembly remains a very difficult problem, made more difficult by shorter reads and unreliable long-range linking information. In this study, we evaluated several of the leading de novo assembly algorithms on four different short-read data sets, all generated by Illumina sequencers. Our results describe the relative performance of the different assemblers as well as other significant differences in assembly difficulty that appear to be inherent in the genomes themselves. Three overarching conclusions are apparent: first, that data quality, rather than the assembler itself, has a dramatic effect on the quality of an assembled genome; second, that the degree of contiguity of an assembly varies enormously among different assemblers and different genomes; and third, that the correctness of an assembly also varies widely and is not well correlated with statistics on contiguity. To enable others to replicate our results, all of our data and methods are freely available, as are all assemblers used in this study.

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Available from: Steven Salzberg, Sep 17, 2015
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    • "All rights reserved. set has inspired several benchmarking approaches, such as the Assemblathons (Earl et al. 2011; Bradnam et al. 2013), Gage (Salzberg et al. 2012; Magoc et al. 2013) and most recently CAMI (http://www.camichallenge .org). "
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    • "additional complications inherent in obtaining genomes using these approaches (Dick et al. 2010; Albertsen et al. 2013). The quality of isolate genomes has traditionally been evaluated using assembly statistics such as N50 (Salzberg et al. 2012; Gurevich et al. 2013), while single cell and metagenomic studies have relied on the presence and absence of universal single-copy 'marker' genes for estimating genome completeness (Wrighton et al. 2012; Haroon et al. 2013; Rinke et al. 2013; Sharon 65 et al. 2013). However, the accuracy of this completeness estimate has not been evaluated and the approach is likely to be limited by both the uneven distribution of universal marker genes across a genome and their low number, typically accounting for <10% of all genes (Sharon and Banfield 2013). "
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    • "We performed de novo assembly of the short reads in the program Abyss v. 1.3 (Simpson et al. 2009). Based on previous studies (Salzberg et al. 2012; Briscoe et al. 2013) and preliminary results (S. Baxter, pers. "
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