Icarus: visualizer for 
            <i>de novo</i>
             assembly evaluation

Mikheenko, Alla; Valin, Gleb; Prjibelski, Andrey D.; Saveliev, Vladislav; Gurevich, Alexey

doi:10.1093/bioinformatics/btw379

Cited by 123 publications

(84 citation statements)

References 16 publications

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“…Purple/blue indicates same/reverse strand matches. C: Icarus(Mikheenko et al 2016) visualization of contig alignments from both HiFibased (Canu, HiCanu, Peregrine) and ultra-long Nanopore-based assemblies (Canu ONT and Flye ONT(Kolmogorov et al 2019)) produced by QUAST(Gurevich et al 2013). White space in the alignment figure indicates the assembly was fragmented into short contigs (<50 kbp).…”

mentioning

confidence: 99%

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

Nurk

Walenz

Rhie

et al. 2020

Preprint

140

227

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Complete and accurate genome assemblies form the basis of most downstream genomic analyses and are of critical importance. Recent genome assembly projects have relied on a combination of noisy long-read sequencing and accurate short-read sequencing, with the former offering greater assembly continuity and the latter providing higher consensus accuracy. The recently introduced PacBio HiFi sequencing technology bridges this divide by delivering long reads (>10 kbp) with high per-base accuracy (>99.9%). Here we present HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering. We benchmark HiCanu with a focus on the recovery of haplotype diversity, major histocompatibility complex (MHC) variants, satellite DNAs, and segmental duplications. For diploid human genomes sequenced to 30× HiFi coverage, HiCanu achieved superior accuracy and allele recovery compared to the current state of the art. On the effectively haploid CHM13 human cell line, HiCanu achieved an NG50 contig size of 77 Mbp with a per-base consensus accuracy of 99.999% (QV50), surpassing recent assemblies of high-coverage, ultra-long Oxford Nanopore reads in terms of both accuracy and continuity. This HiCanu assembly correctly resolves 337 out of 341 validation BACs sampled from known segmental duplications and provides the first preliminary assemblies of 9 complete human centromeric regions. Although gaps and errors still remain within the most challenging regions of the genome, these results represent a significant advance towards the complete assembly of human genomes.Availability: HiCanu is implemented within the Canu assembly framework and is available from https://github.com/marbl/canu. This required 7 CPU h and 29 GB of memory for D. melanogaster, 32 CPU h and 347 GB of memory for CHM13 10 kbp library, 58 CPU h and 449 GB of memory for CHM13 20 kbp library, 55 CPU h and 407 GB for HG0002, and 63 CPU h and 477 GB for HG00733. Commands for β-defensin validation:MUmmer 3.23 was used to identify repeats with the command: nucmer --maxmatch --nosimplify delta-filter -i 98 -l 10000

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mentioning

confidence: 99%

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

Nurk

Walenz

Rhie

et al. 2020

Preprint

140

227

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“…We filtered the assemblies based on contigs length (> 500 bp) and SPAdes coverage (> or = 2). Then, each assembly was mapped against the corresponding complete chromosome and plasmid sequences from the NCBI database using Quast 4.6 with standard parameters (13). Contigs that did not aligned on any sequence (chromosome and plasmid) or aligned on less than 50% of their length were not considered, as well as contigs that aligned on both sequences.…”

Section: Reference Dataset For Methods Evaluationmentioning

confidence: 99%

PlaScope: a targeted approach to assess the plasmidome of Escherichia coli strains

Royer

Decousser

Branger

et al. 2018

Preprint

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Plasmid prediction may be of great interest when studying bacteria such as Enterobacteriaceae. Indeed many resistance and virulence genes are located on such replicons and can have major impact in terms of pathogenicity and spreading capacities.Beyond strains outbreak, plasmids outbreaks have been reported especially for some extended-spectrum beta-lactamase or carbapenemase producing Enterobacteriaceae.Several tools are now available to explore the "plasmidome" from whole-genome sequence data, with many interesting and various approaches. However recent benchmarks have highlighted that none of them succeed to combine high sensitivity and specificity. With this in mind we developed PlaScope, a targeted approach to recover plasmidic sequences in Escherichia coli. Based on Centrifuge, a metagenomic classifier, and a custom database containing complete sequences of chromosomes and plasmids from various curated databases, it performs a classification of contigs from an assembly according to their predicted location. Compared to other plasmid classifiers, Plasflow and cBar, it achieves better recall (0.87), specificity (0.99), precision (0.96) and accuracy (0.98) on a dataset of 70 genomes containing plasmids. Finally we tested our method on a dataset of E. coli strains exhibiting an elevated rate of extended-spectrum beta-lactamase coding gene chromosomal integration, and we were able to identify 20/21 of these events. Moreover virulence genes and operons predicted locations were also in agreement with the literature. Similar approaches could also be developed for other well-characterized bacteria such as Klebsiella pneumoniae. Data summary1. All the genomes were downloaded from the National Center for Biotechnology Information Sequence Read Archive and Genome database (Supplementary table 1 and 2). The source code of PlaScope is available on Github(https://github.com/GuilhemRoyer/PlaScope). ImportancePlasmid exploration could be of great interest since these replicons are pivotal in the adaptation of bacteria to their environment. They are involved in the exchange of many genes within and between species, with a significant impact on antibiotic resistance and virulence in particular. However, plasmid characterization has been a laborious task for many years, requiring complex conjugation or electroporation manipulations for example.With the advent of whole genome sequencing techniques, access to these sequences is now potentially easier provided that appropriate tools are available. Many softwares have been developed to explore the plasmidome of a large variety of bacteria, but they rarely managed to combine sensitivity and specificity. Here, we focus on a single species, E. coli, and we use the many data available to overcome this problem. With our tool called PlaScope, we achieve high performance compared with two other classifiers, Plasflow and cBar, and we demonstrate the utility of such an approach to determine the location of virulence or resistance genes. We think that PlaScope could be very useful in the ana...

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“…Although several tools exist for evaluating and visualizing the quality of genome assemblies like QUAST-LG [11], Icarus [12], LASER [13], REAPR [14], they are challenging to install and configure, do not support assessment of gene structure annotations, and do not determine the completeness of the repetitive fraction of the genome based on LTR retrotransposon content.…”

Section: Comparison With Similar Software Programsmentioning

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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Icarus: visualizer for de novo assembly evaluation

Abstract: http://cab.spbu.ru/software/icarus CONTACT: aleksey.gurevich@spbu.ruSupplementary information: Supplementary data are available at Bioinformatics online.

Cited by 123 publications

References 16 publications

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

PlaScope: a targeted approach to assess the plasmidome of Escherichia coli strains

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

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