A comparative evaluation of genome assembly reconciliation tools

Abstract

BackgroundThe majority of eukaryotic genomes are unfinished due to the algorithmic challenges of assembling them. A variety of assembly and scaffolding tools are available, but it is not always obvious which tool or parameters to use for a specific genome size and complexity. It is, therefore, common practice to produce multiple assemblies using different assemblers and parameters, then select the best one for public release. A more compelling approach would allow one to merge multiple assemblies with the intent of producing a higher quality consensus assembly, which is the objective of assembly reconciliation.ResultsSeveral assembly reconciliation tools have been proposed in the literature, but their strengths and weaknesses have never been compared on a common dataset. We fill this need with this work, in which we report on an extensive comparative evaluation of several tools. Specifically, we evaluate contiguity, correctness, coverage, and the duplication ratio of the merged assembly compared to the individual assemblies provided as input.ConclusionsNone of the tools we tested consistently improved the quality of the input GAGE and synthetic assemblies. Our experiments show an increase in contiguity in the consensus assembly when the original assemblies already have high quality. In terms of correctness, the quality of the results depends on the specific tool, as well as on the quality and the ranking of the input assemblies. In general, the number of misassemblies ranges from being comparable to the best of the input assembly to being comparable to the worst of the input assembly.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1213-3) contains supplementary material, which is available to authorized users.

NucMerge: Genome assembly quality improvement assisted by alternative assemblies and paired-end Illumina reads

“…We excluded the GAA and Reconciliator tools from the testing. GAA had already been compared to GAM-NGS in [13] and [31]. In both cases, GAA showed its predisposition to introduction of structural rearrangements and duplication errors.…”

Graph analysis of fragmented long-read bacterial genome assemblies

“…We also did not focus on the difficulty of running multiple assembly programs, but we note that the process has previously been reported to be challenging (Lariviere et al, 2018). Our work is also orthogonal to assembly reconciliation (Alhakami et al, 2017), which consists of constructing a higher-contiguity assembly by merging the results of multiple assemblers.…”

The new era of genome sequencing using high-throughput sequencing technology: generation of the first version of the Atlantic cod genome

“…Both ALLPATHS-LG and Celera Assembler implements tools to correct the errors in the reads, creating more accurate reads before assembly, but standalone tools also exists (Alic et al, 2016). A third path is to create several draft assemblies that could be merged or reconciled with Metassembler (Wences and Schatz, 2015) or a similar reconciliation tool (Alhakami et al, 2017). There are also tools specifically created to use paired Illumina reads to close gaps, IMAGE (Tsai et al, 2010) and GapFiller (Nadalin et al, 2012).…”