scholarly journals Scalable Genome Assembly through Parallel de Bruijn Graph Construction for Multiple k-mers

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kanak Mahadik ◽  
Christopher Wright ◽  
Milind Kulkarni ◽  
Saurabh Bagchi ◽  
Somali Chaterji
Keyword(s):  
De Novo ◽  
De Bruijn Graph ◽  
High Quality ◽  
De Bruijn Graphs ◽  
Sequencing Technologies ◽  
De Bruijn ◽  
Similar Accuracy ◽  
Valued Graph ◽  
Assembly Algorithms ◽  
Level Parallelism

Abstract Remarkable advancements in high-throughput gene sequencing technologies have led to an exponential growth in the number of sequenced genomes. However, unavailability of highly parallel and scalable de novo assembly algorithms have hindered biologists attempting to swiftly assemble high-quality complex genomes. Popular de Bruijn graph assemblers, such as IDBA-UD, generate high-quality assemblies by iterating over a set of k-values used in the construction of de Bruijn graphs (DBG). However, this process of sequentially iterating from small to large k-values slows down the process of assembly. In this paper, we propose ScalaDBG, which metamorphoses this sequential process, building DBGs for each distinct k-value in parallel. We develop an innovative mechanism to “patch” a higher k-valued graph with contigs generated from a lower k-valued graph. Moreover, ScalaDBG leverages multi-level parallelism, by both scaling up on all cores of a node, and scaling out to multiple nodes simultaneously. We demonstrate that ScalaDBG completes assembling the genome faster than IDBA-UD, but with similar accuracy on a variety of datasets (6.8X faster for one of the most complex genome in our dataset).

Population-scale detection of non-reference sequence variants using colored de Bruijn Graphs

2021 ◽  
Author(s):  
Thomas Krannich ◽  
Walton Timothy James White ◽  
Sebastian Niehus ◽  
Guillaume Holley ◽  
Bjarni Halldorsson ◽  
...  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Simulated Data ◽  
Reference Sequence ◽  
De Bruijn Graph ◽  
High Coverage ◽  
De Bruijn Graphs ◽  
Sequencing Technologies ◽  
De Bruijn ◽  
Population Scale

With the increasing throughput of sequencing technologies, structural variant (SV) detection has become possible across ten of thousands of genomes. Non-reference sequence (NRS) variants have drawn less attention compared to other types of SVs due to the computational complexity of detecting them. When using short-read data the detection of NRS variants inevitably involves a de novo assembly which requires high-quality sequence data at high coverage. Previous studies have demonstrated how sequence data of multiple genomes can be combined for the reliable detection of NRS variants. However, the algorithms proposed in these studies have limited scalability to larger sets of genomes. We introduce PopIns2, a tool to discover and characterize NRS variants in many genomes, which scales to considerably larger numbers of genomes than its predecessor PopIns. In this article, we briefly outline the workflow of PopIns and highlight the novel algorithmic contributions. We developed an entirely new approach for merging contig assemblies of unaligned reads from many genomes into a single set of NRS using a colored de Bruijn graph. Our tests on simulated data indicate that the new merging algorithm ranks among the best approaches in terms of quality and reliability and that PopIns2 shows the best precision for a growing number of genomes processed. Results on the Polaris Diversity Cohort and a set of 1000 Icelandic human genomes demonstrate unmatched scalability for the application on population-scale datasets.

scholarly journals Clover: a clustering-oriented de novo assembler for Illumina sequences

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ming-Feng Hsieh ◽  
Chin Lung Lu ◽  
Chuan Yi Tang
Keyword(s):  
De Novo Assembly ◽  
De Novo ◽  
Low Cost ◽  
De Bruijn Graph ◽  
Illumina Platform ◽  
Sequencing Errors ◽  
Sequencing Technologies ◽  
String Graph ◽  
Clustering Approach ◽  
De Bruijn

Abstract Background Next-generation sequencing technologies revolutionized genomics by producing high-throughput reads at low cost, and this progress has prompted the recent development of de novo assemblers. Multiple assembly methods based on de Bruijn graph have been shown to be efficient for Illumina reads. However, the sequencing errors generated by the sequencer complicate analysis of de novo assembly and influence the quality of downstream genomic researches. Results In this paper, we develop a de Bruijn assembler, called Clover (clustering-oriented de novo assembler), that utilizes a novel k-mer clustering approach from the overlap-layout-consensus concept to deal with the sequencing errors generated by the Illumina platform. We further evaluate Clover’s performance against several de Bruijn graph assemblers (ABySS, SOAPdenovo, SPAdes and Velvet), overlap-layout-consensus assemblers (Bambus2, CABOG and MSR-CA) and string graph assembler (SGA) on three datasets (Staphylococcus aureus, Rhodobacter sphaeroides and human chromosome 14). The results show that Clover achieves a superior assembly quality in terms of corrected N50 and E-size while remaining a significantly competitive in run time except SOAPdenovo. In addition, Clover was involved in the sequencing projects of bacterial genomes Acinetobacter baumannii TYTH-1 and Morganella morganii KT. Conclusions The marvel clustering-based approach of Clover that integrates the flexibility of the overlap-layout-consensus approach and the efficiency of the de Bruijn graph method has high potential on de novo assembly. Now, Clover is freely available as open source software from https://oz.nthu.edu.tw/~d9562563/src.html.

Inference of viral quasispecies with a paired de Bruijn graph

2020 ◽  
Author(s):  
Borja Freire ◽  
Susana Ladra ◽  
Jose R Paramá ◽  
Leena Salmela
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Supplementary Information ◽  
De Bruijn Graph ◽  
Viral Quasispecies ◽  
Sequencing Data ◽  
De Bruijn Graphs ◽  
Sequencing Errors ◽  
High Throughput Sequencing Data ◽  
De Bruijn

Abstract Motivation RNA viruses exhibit a high mutation rate and thus they exist in infected cells as a population of closely related strains called viral quasispecies. The viral quasispecies assembly problem asks to characterize the quasispecies present in a sample from high-throughput sequencing data. We study the de novo version of the problem, where reference sequences of the quasispecies are not available. Current methods for assembling viral quasispecies are either based on overlap graphs or on de Bruijn graphs. Overlap graph-based methods tend to be accurate but slow, whereas de Bruijn graph-based methods are fast but less accurate. Results We present viaDBG, which is a fast and accurate de Bruijn graph-based tool for de novo assembly of viral quasispecies. We first iteratively correct sequencing errors in the reads, which allows us to use large k-mers in the de Bruijn graph. To incorporate the paired-end information in the graph, we also adapt the paired de Bruijn graph for viral quasispecies assembly. These features enable the use of long-range information in contig construction without compromising the speed of de Bruijn graph-based approaches. Our experimental results show that viaDBG is both accurate and fast, whereas previous methods are either fast or accurate but not both. In particular, viaDBG has comparable or better accuracy than SAVAGE, while being at least nine times faster. Furthermore, the speed of viaDBG is comparable to PEHaplo but viaDBG is able to retrieve also low abundance quasispecies, which are often missed by PEHaplo. Availability and implementation viaDBG is implemented in C++ and it is publicly available at https://bitbucket.org/bfreirec1/viadbg. All datasets used in this article are publicly available at https://bitbucket.org/bfreirec1/data-viadbg/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Haploflow: Strain-resolved de novo assembly of viral genomes

2021 ◽  
Author(s):  
A. Fritz ◽  
A. Bremges ◽  
Z.-L. Deng ◽  
T.-R. Lesker ◽  
J. Götting ◽  
...  
Keyword(s):  
Viral Infections ◽  
De Novo ◽  
De Bruijn Graph ◽  
Data Sets ◽  
High Quality ◽  
Viral Genomes ◽  
Benchmark Data ◽  
Flow Algorithm ◽  
De Bruijn ◽  
Host Evolution

In viral infections often multiple related viral strains are present, due to coinfection or within-host evolution. We describe Haploflow, a de Bruijn graph-based assembler for de novo genome assembly of viral strains from mixed sequence samples using a novel flow algorithm. We assessed Haploflow across multiple benchmark data sets of increasing complexity, showing that Haploflow is faster and more accurate than viral haplotype assemblers and generic metagenome assemblers not aiming to reconstruct strains. Haplotype reconstructed high-quality strain-resolved assemblies from clinical HCMV samples and SARS-CoV-2 genomes from wastewater metagenomes identical to genomes from clinical isolates.

scholarly journals BubbleGun: Enumerating Bubbles and Superbubbles in Genome Graphs

2021 ◽  
Author(s):  
Fawaz Dabbaghie ◽  
Jana Ebler ◽  
Tobias Marschall
Keyword(s):  
De Novo ◽  
General Purpose ◽  
Supplementary Information ◽  
De Bruijn Graph ◽  
De Bruijn Graphs ◽  
Third Generation Sequencing ◽  
Human Sample ◽  
Fast Development ◽  
De Bruijn ◽  
Generation Sequencing

AbstractMotivationWith the fast development of third generation sequencing machines, de novo genome assembly is becoming a routine even for larger genomes. Graph-based representations of genomes arise both as part of the assembly process, but also in the context of pangenomes representing a population. In both cases, polymorphic loci lead to bubble structures in such graphs. Detecting bubbles is hence an important task when working with genomic variants in the context of genome graphs.ResultsHere, we present a fast general-purpose tool, called BubbleGun, for detecting bubbles and superbubbles in genome graphs. Furthermore, BubbleGun detects and outputs runs of linearly connected bubbles and superbubbles, which we call bubble chains. We showcase its utility on de Bruijn graphs and compare our results to vg’s snarl detection. We show that BubbleGun is considerably faster than vg especially in bigger graphs, where it reports all bubbles in less than 30 minutes on a human sample de Bruijn graph of around 2 million nodes.AvailabilityBubbleGun is available and documented at https://github.com/fawaz-dabbaghieh/bubble_gun under MIT [email protected] or [email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals HINGE: Long-Read Assembly Achieves Optimal Repeat Resolution

2016 ◽  
Author(s):  
Govinda M. Kamath ◽  
Ilan Shomorony ◽  
Fei Xia ◽  
Thomas A. Courtade ◽  
David N. Tse
Keyword(s):  
Gold Standard ◽  
De Novo ◽  
Error Resilience ◽  
De Bruijn Graph ◽  
Sequencing Technologies ◽  
Long Read ◽  
De Bruijn ◽  
Genome Assemblies

ABSTRACTLong-read sequencing technologies have the potential to produce gold-standard de novo genome assemblies, but fully exploiting error-prone reads to resolve repeats remains a challenge. Aggressive approaches to repeat resolution often produce mis-assemblies, and conservative approaches lead to unnecessary fragmentation. We present HINGE, an assembler that seeks to achieve optimal repeat resolution by distinguishing repeats that can be resolved given the data from those that cannot. This is accomplished by adding "hinges" to reads for constructing an overlap graph where only unresolvable repeats are merged. As a result, HINGE combines the error resilience of overlap-based assemblers with repeat-resolution capabilities of de Bruijn graph assemblers. HINGE was evaluated on the long-read bacterial datasets from the NCTC project. HINGE produces more finished assemblies than Miniasm and the manual pipeline of NCTC based on the HGAP assembler and Circlator. HINGE also allows us to identify 40 datasets where unresolvable repeats prevent the reliable construction of a unique finished assembly. In these cases, HINGE outputs a visually interpretable assembly graph that encodes all possible finished assemblies consistent with the reads, while other approaches such as the NCTC pipeline and FALCON either fragment the assembly or resolve the ambiguity arbitrarily.

scholarly journals MBG: Minimizer-based Sparse de Bruijn Graph Construction

2020 ◽  
Author(s):  
Mikko Rautiainen ◽  
Tobias Marschall
Keyword(s):  
Source Code ◽  
Error Rates ◽  
Read Length ◽  
De Bruijn Graph ◽  
De Bruijn Graphs ◽  
E Coli ◽  
Link Type ◽  
Sequencing Technologies ◽  
Long Read ◽  
De Bruijn

MotivationDe Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally long read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads.ResultsWe have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs, and can build a graph of 50x coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterial E. coli genome into a single contig in 8 seconds.AvailabilityPackage manager: https://anaconda.org/bioconda/mbg and source code: https://github.com/maickrau/MBG

scholarly journals Assembling Long Accurate Reads Using de Bruijn Graphs

2020 ◽  
Author(s):  
Anton Bankevich ◽  
Andrey Bzikadze ◽  
Mikhail Kolmogorov ◽  
Pavel A. Pevzner
Keyword(s):  
Human Genome ◽  
De Bruijn Graph ◽  
High Fidelity ◽  
High Quality ◽  
De Bruijn Graphs ◽  
String Graph ◽  
De Bruijn ◽  
Genome Assembler ◽  
Large Genomes

AbstractAlthough the de Bruijn graphs represent the basis of many genome assemblers, it remains unclear how to construct these graphs for large genomes and large k-mer sizes. This algorithmic challenge has become particularly important with the emergence of long and accurate high-fidelity (HiFi) reads that were recently utilized to generate a semi-manual telomere-to-telomere assembly of the human genome using the alternative string graph assembly approach. To enable fully automated high-quality HiFi assemblies of various genomes, we developed an efficient jumboDB algorithm for constructing the de Bruijn graph for large genomes and large k-mer sizes and the LJA genome assembler that error-corrects HiFi reads and uses jumboDB to construct the de Bruijn graph on the error-corrected reads. Since the de Bruijn graph constructed for a fixed k-mer size is typically either too tangled or too fragmented, LJA uses a new concept of a multiplex de Bruijn graph with varying k-mer sizes. We demonstrate that LJA produces contiguous assemblies of complex repetitive regions in genomes including automated assemblies of various highly-repetitive human centromeres.

scholarly journals Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird-of-paradise

2019 ◽  
Author(s):  
Valentina Peona ◽  
Mozes P.K. Blom ◽  
Luohao Xu ◽  
Reto Burri ◽  
Shawn Sullivan ◽  
...  
Keyword(s):  
Dark Matter ◽  
Genome Assembly ◽  
Sex Chromosome ◽  
De Novo ◽  
Model Organism ◽  
Technology Choice ◽  
High Quality ◽  
Sequencing Technologies ◽  
Downstream Analysis ◽  
Genome Assemblies

AbstractGenome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies have opened up a whole new world of genomic biodiversity. Although these technologies generate high-quality genome assemblies, there are still genomic regions difficult to assemble, like repetitive elements and GC-rich regions (genomic “dark matter”). In this study, we compare the efficiency of currently used sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter starting from the same sample. By adopting different de-novo assembly strategies, we were able to compare each individual draft assembly to a curated multiplatform one and identify the nature of the previously missing dark matter with a particular focus on transposable elements, multi-copy MHC genes, and GC-rich regions. Thanks to this multiplatform approach, we demonstrate the feasibility of producing a high-quality chromosome-level assembly for a non-model organism (paradise crow) for which only suboptimal samples are available. Our approach was able to reconstruct complex chromosomes like the repeat-rich W sex chromosome and several GC-rich microchromosomes. Telomere-to-telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects around the completeness of both the coding and non-coding parts of the genomes.

scholarly journals LeafGo: Leaf to Genome, a quick workflow to produce high-quality De novo genomes with Third Generation Sequencing technology

2021 ◽  
Author(s):  
Patrick Driguez ◽  
Salim Bougouffa ◽  
Karen Carty ◽  
Alexander Putra ◽  
Kamel Jabbari ◽  
...  
Keyword(s):  
De Novo ◽  
Rapid Development ◽  
Plant Genome ◽  
Plant Genomics ◽  
High Quality ◽  
High Molecular Weight Dna ◽  
Tissue Samples ◽  
Sequencing Technologies ◽  
The Cost ◽  
New Generation

AbstractRecent years have witnessed a rapid development of sequencing technologies. Fundamental differences and limitations among various platforms impact the time, the cost and the accuracy for sequencing whole genomes. Here we designed a complete de novo plant genome generation workflow that starts from plant tissue samples and produces high-quality draft genomes with relatively modest laboratory and bioinformatic resources within seven days. To optimize our workflow we selected different species of plants which were used to extract high molecular weight DNA, to make PacBio and ONT libraries for sequencing with the Sequel I, Sequel II and GridION platforms. We assembled high-quality draft genomes of two different Eucalyptus species E. rudis, and E. camaldulensis to chromosome level without using additional scaffolding technologies. For the rapid production of de novo genome assembly of plant species we showed that our DNA extraction protocol followed by PacBio high fidelity sequencing, and assembly with new generation assemblers such as hifiasm produce excellent results. Our findings will be a valuable benchmark for groups planning wet- and dry-lab plant genomics research and for high throughput plant genomics initiatives.

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