Abstract
In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental “features” of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed , which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers – thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.
Highlights
The extraordinary advances in Generation Sequencing (NGS) technologies over the last ten years have triggered an exponential drop in sequencing cost, making it possible to perform whole-genome shotgun (WGS) sequencing of almost every organism in the biosphere
Description low read coverage areas. high read coverage areas. low paired-read coverage areas. high paired-read coverage areas. low CE-statistics computed on paired-end library (PE)-reads. high CE-statistics computed on PE-reads. high number of PE reads with unmapped pair. high number of PE reads with pair mapped in a different contig/scaffold. high number of mis-oriented or too distant PE reads. low CE-statistics computed on mated-pair library (MP) reads. high CE-statistics computed on MP reads. high number of MP reads with unmapped pair. high number of MP reads with pair mapped in a different contig/scaffold. high number of mis-oriented or too distant MP reads
For each assembler we report the number of contigs/scaffolds produced (Ctg), the NG50, the percentage of short (Chaff) contigs, the number of long (i.e., .5 bp) indels (Indels), the number of Misjoins, the number of inversions (Inv), the number of relocations (Rel), the features sensitivity (Sens), and the features specificity (Spec). doi:10.1371/journal.pone.0052210.t002
Summary
The extraordinary advances in Generation Sequencing (NGS) technologies over the last ten years have triggered an exponential drop in sequencing cost, making it possible to perform whole-genome shotgun (WGS) sequencing of almost every organism in the biosphere. Recent WGS projects are distinctive by the way they have facilitated whole genome sequencing at a high coverage (i.e., higher than 506), albeit, composed of relatively short sequences (i.e., reads) Despite this impressive progress, recent efforts have underlined the difficulties in trading-off read length against read coverage. It is well recognized how the short reads have made the assembly problem significantly harder [1] owing to the complexity involved in resolving (i.e., span over) long repeats This challenge has been confronted recently with sophisticated and novel techniques, embedded in a diverse set of tools all aiming to solve de novo assembly problem. Additional heuristics are employed for error correction and read-culling
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
