Genome Assembly Pipeline Research Articles

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BackgroundImplementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.ResultsThe routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a “generic” build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.ConclusionsThe accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Constructing telomere-to-telomere diploid genome by polishing haploid nanopore-based assembly.

Draft genomes generated from Oxford Nanopore Technologies (ONT) long reads are known to have a higher error rate. Although existing genome polishers can enhance their quality, the error rate (including mismatches, indels and switching errors between paternal and maternal haplotypes) can be significant. Here, we develop two polishers, hypo-short and hypo-hybrid to address this issue. Hypo-short utilizes Illumina short reads to polish an ONT-based draft assembly, resulting in a high-quality assembly with low error rates and switching errors. Expanding on this, hypo-hybrid incorporates ONT long reads to further refine the assembly into a diploid representation. Leveraging on hypo-hybrid, we have created a diploid genome assembly pipeline called hypo-assembler. Hypo-assembler automates the generation of highly accurate, contiguous and nearly complete diploid assemblies using ONT long reads, Illumina short reads and optionally Hi-C reads. Notably, our solution even allows for the production of telomere-to-telomere diploid genomes with additional manual steps. As a proof of concept, we successfully assembled a fully phased telomere-to-telomere diploid genome of HG00733, achieving a quality value exceeding 50.

First Steps towards Efficient Genome Assembly on ARM-Based HPC

Exponential advances in computational power have fueled advances in many disciplines, and biology is no exception. High-Performance Computing (HPC) is gaining traction as one of the essential tools in scientific research. Further advances to exascale capabilities will necessitate more energy-efficient hardware. In this article, we present our efforts to improve the efficiency of genome assembly on ARM-based HPC systems. We use vectorization to optimize the popular genome assembly pipeline of minimap2, miniasm, and Racon. We compare different implementations using the Scalable Vector Extension (SVE) instruction set architecture and evaluate their performance in different aspects. Additionally, we compare the performance of autovectorization to hand-tuned code with intrinsics. Lastly, we present the design of a CPU dispatcher included in the Racon consensus module that enables the automatic selection of the fastest instruction set supported by the utilized CPU. Our findings provide a promising direction for further optimization of genome assembly on ARM-based HPC systems.

Folding Features and Dynamics of 3D Genome Architecture in Plant Fungal Pathogens.

The folding and dynamics of three-dimensional (3D) genome organization are fundamental for eukaryotes executing genome functions but have been largely unexplored in nonmodel fungi. Using high-throughput sequencing coupled with chromosome conformation capture (Hi-C) data, we generated two chromosome-level assemblies for Puccinia striiformis f. sp. tritici, a fungus causing stripe rust disease on wheat, for studying 3D genome architectures of plant pathogenic fungi. The chromatin organization of the fungus followed a combination of the fractal globule model and the equilibrium globule model. Surprisingly, chromosome compartmentalization was not detected. Dynamics of 3D genome organization during two developmental stages of P. striiformis f. sp. tritici indicated that regulation of gene activities might be independent of the changes of genome organization. In addition, chromatin conformation conservation was found to be independent of genome sequence synteny conservation among different fungi. These results highlighted the distinct folding principles of fungal 3D genomes. Our findings should be an important step toward a holistic understanding of the principles and functions of genome architecture across different eukaryotic kingdoms. IMPORTANCE Previously, our understanding of 3D genome architecture has mainly come from model mammals, insects, and plants. However, the organization and regulatory functions of 3D genomes in fungi are largely unknown. In this study, we comprehensively investigated P. striiformis f. sp. tritici, a plant fungal pathogen, and revealed distinct features of the 3D genome, comparing it with the universal folding feature of 3D genomes in higher eukaryotic organisms. We further suggested that there might be distinct regulatory mechanisms of gene expression that are independent of chromatin organization changes during the developmental stages of this rust fungus. Moreover, we showed that the evolutionary pattern of 3D genomes in this fungus is also different from the cases in mammalian genomes. In addition, the genome assembly pipeline and the generated two chromosome-level genomes will be valuable resources. These results highlighted the unexplored distinct features of 3D genome organization in fungi. Therefore, our study provided complementary knowledge to holistically understand the organization and functions of 3D genomes across different eukaryotes.

Karyon: a computational framework for the diagnosis of hybrids, aneuploids, and other nonstandard architectures in genome assemblies.

BackgroundRecent technological developments have made genome sequencing and assembly highly accessible and widely used. However, the presence in sequenced organisms of certain genomic features such as high heterozygosity, polyploidy, aneuploidy, heterokaryosis, or extreme compositional biases can challenge current standard assembly procedures and result in highly fragmented assemblies. Hence, we hypothesized that genome databases must contain a nonnegligible fraction of low-quality assemblies that result from such type of intrinsic genomic factors.FindingsHere we present Karyon, a Python-based toolkit that uses raw sequencing data and de novo genome assembly to assess several parameters and generate informative plots to assist in the identification of nonchanonical genomic traits. Karyon includes automated de novo genome assembly and variant calling pipelines. We tested Karyon by diagnosing 35 highly fragmented publicly available assemblies from 19 different Mucorales (Fungi) species.ConclusionsOur results show that 10 (28.57%) of the assemblies presented signs of unusual genomic configurations, suggesting that these are common, at least for some lineages within the Fungi.

GcaPDA: a haplotype-resolved diploid assembler

BackgroundGenerating chromosome-scale haplotype resolved assembly is important for functional studies. However, current de novo assemblers are either haploid assemblers that discard allelic information, or diploid assemblers that can only tackle genomes of low complexity.ResultsHere, Using robust programs, we build a diploid genome assembly pipeline called gcaPDA (gamete cells assisted Phased Diploid Assembler), which exploits haploid gamete cells to assist in resolving haplotypes. We demonstrate the effectiveness of gcaPDA based on simulated HiFi reads of maize genome which is highly heterozygous and repetitive, and real data from rice.ConclusionsWith applicability of coping with complex genomes and fewer restrictions on application than most of diploid assemblers, gcaPDA is likely to find broad applications in studies of eukaryotic genomes.

MicroPIPE: validating an end-to-end workflow for high-quality complete bacterial genome construction

BackgroundOxford Nanopore Technology (ONT) long-read sequencing has become a popular platform for microbial researchers due to the accessibility and affordability of its devices. However, easy and automated construction of high-quality bacterial genomes using nanopore reads remains challenging. Here we aimed to create a reproducible end-to-end bacterial genome assembly pipeline using ONT in combination with Illumina sequencing.ResultsWe evaluated the performance of several popular tools used during genome reconstruction, including base-calling, filtering, assembly, and polishing. We also assessed overall genome accuracy using ONT both natively and with Illumina. All steps were validated using the high-quality complete reference genome for the Escherichia coli sequence type (ST)131 strain EC958. Software chosen at each stage were incorporated into our final pipeline, MicroPIPE.Further validation of MicroPIPE was carried out using 11 additional ST131 E. coli isolates, which demonstrated that complete circularised chromosomes and plasmids could be achieved without manual intervention. Twelve publicly available Gram-negative and Gram-positive bacterial genomes (with available raw ONT data and matched complete genomes) were also assembled using MicroPIPE. We found that revised basecalling and updated assembly of the majority of these genomes resulted in improved accuracy compared to the current publicly available complete genomes.ConclusionsMicroPIPE is built in modules using Singularity container images and the bioinformatics workflow manager Nextflow, allowing changes and adjustments to be made in response to future tool development. Overall, MicroPIPE provides an easy-access, end-to-end solution for attaining high-quality bacterial genomes. MicroPIPE is available at https://github.com/BeatsonLab-MicrobialGenomics/micropipe.

An exploration of assembly strategies and quality metrics on the accuracy of the rewarewa (Knightia excelsa) genome.

We used long read sequencing data generated from Knightia excelsa, a nectar‐producing Proteaceae tree endemic to Aotearoa (New Zealand), to explore how sequencing data type, volume and workflows can impact final assembly accuracy and chromosome reconstruction. Establishing a high‐quality genome for this species has specific cultural importance to Māori and commercial importance to honey producers in Aotearoa. Assemblies were produced by five long read assemblers using data subsampled based on read lengths, two polishing strategies and two Hi‐C mapping methods. Our results from subsampling the data by read length showed that each assembler tested performed differently depending on the coverage and the read length of the data. Subsampling highlighted that input data with longer read lengths but perhaps lower coverage constructed more contiguous, kmers and gene‐complete assemblies than short read length input data with higher coverage. The final genome assembly was constructed into 14 pseudochromosomes using an initial flye long read assembly, a racon/medaka/pilon combined polishing strategy, salsa2 and allhic scaffolding, juicebox curation, and Macadamia linkage map validation. We highlighted the importance of developing assembly workflows based on the volume and read length of sequencing data and established a robust set of quality metrics for generating high‐quality assemblies. Scaffolding analyses highlighted that problems found in the initial assemblies could not be resolved accurately by Hi‐C data and that assembly scaffolding was more successful when the underlying contig assembly was of higher accuracy. These findings provide insight into how quality assessment tools can be implemented throughout genome assembly pipelines to inform the de novo reconstruction of a high‐quality genome assembly for nonmodel organisms.

PaKman: A Scalable Algorithm for Generating Genomic Contigs on Distributed Memory Machines

De novo genome assembly is a fundamental problem in the field of bioinformatics, that aims to assemble the DNA sequence of an unknown genome from numerous short DNA fragments (aka reads) obtained from it. With the advent of high-throughput sequencing technologies, billions of reads can be generated in a matter of hours, necessitating efficient parallelization of the assembly process. While multiple parallel solutions have been proposed in the past, conducting a large-scale assembly at scale remains a challenging problem because of the inherent complexities associated with data movement, and irregular access footprints of memory and I/O operations. In this article, we present a novel algorithm, called PaKman , to address the problem of performing large-scale genome assemblies on a distributed memory parallel computer. Our approach focuses on improving performance through a combination of novel data structures and algorithmic strategies for reducing the communication and I/O footprint during the assembly process. PaKman presents a solution for the two most time-consuming phases in the full genome assembly pipeline, namely, k-mer counting and contig generation . A key aspect of our algorithm is its graph data structure (PaK-Graph), which comprises fat nodes (or what we call “macro-nodes”) that reduce the communication burden during contig generation. We present an extensive performance and qualitative evaluation of our algorithm across a wide range of genomes (varying in both size and species group), including comparisons to other state-of-the-art parallel assemblers. Our results demonstrate the ability to achieve near-linear speedups on up to 16K cores (tested) on the NERSC Cori supercomputer; perform better than or comparable to other state-of-the-art distributed memory and shared memory tools in terms of performance while delivering comparable (if not better) quality; and reduce time to solution significantly. For instance, PaKman is able to generate a high-quality set of assembled contigs for complex genomes such as the human and bread wheat genomes in under a minute on 16K cores. In addition, PaKman was able to successfully process a 3.1 TB simulated dataset of one of the largest known genomes (to date)- Ambystoma mexicanum (the axolotl), in just over 200 seconds on 16K cores.

A simple method for high molecular-weight genomic DNA extraction suitable for long-read sequencing from spores of an obligate biotroph oomycete

Long-read sequencing technologies are having a major impact on our approaches to studying non-model organisms and microbial communities. By significantly reducing the cost and facilitating the genome assembly pipelines, any laboratory can now develop its own genomics program regardless of the complexity of the genome studied. The most crucial current challenge is to develop efficient protocols for extracting genomic DNA (gDNA) with high quality and integrity adapted to the organism of interest. This can be particularly complex for obligate pathogens that must maintain intimate interactions inside infected host tissues. Here we propose a simple and cost-effective method for high molecular weight gDNA extraction from spores of Plasmopara halstedii, an obligate biotroph oomycete pathogen responsible for downy mildew in sunflower. We optimized the yield, the quality and the integrity of the extracted gDNA by fine-tuning three critical parameters, the grinding, the lysis temperature and the lysis duration. We obtained gDNA with a fragment size distribution reaching a peak ranging from 79 to 145 kb. More than half of the extracted gDNA consisted of DNA fragments larger than 42 kb, with 23% of fragments larger than 100 kb. We then demonstrated the relevance of this protocol for long-read sequencing using PacBio RSII technology. With this protocol, we were able to obtain a mean read length of 9.3 kb, a max read length of 71 kb and an N50 of 13.3 kb. The development of such DNA extraction protocols is an essential prerequisite for fully exploiting technologies requiring high molecular weight gDNA (e.g. long-read sequencing or optical mapping). These technological advances will help generate data to answer questions such as the role of newly duplicated gene clusters, repeated regions, genomic structural variations or to define number of chromosomes that still remains undefined in many species of pathogenic fungi and oomycetes.

De Novo Assembly of a High-Quality Reference Genome for the Horned Lark (Eremophila alpestris).

The Horned Lark (Eremophila alpestris) is a small songbird that exhibits remarkable geographic variation in appearance and habitat across an expansive distribution. While E. alpestris has been the focus of many ecological and evolutionary studies, we still lack a highly contiguous genome assembly for the Horned Lark and related taxa (Alaudidae). Here, we present CLO_EAlp_1.0, a highly contiguous assembly for E. alpestris generated from a blood sample of a wild, male bird captured in the Altiplano Cundiboyacense of Colombia. By combining short-insert and mate-pair libraries with the ALLPATHS-LG genome assembly pipeline, we generated a 1.04 Gb assembly comprised of 2713 scaffolds, with a largest scaffold size of 31.81 Mb, a scaffold N50 of 9.42 Mb, and a scaffold L50 of 30. These scaffolds were assembled from 23685 contigs, with a largest contig size of 1.69 Mb, a contig N50 of 193.81 kb, and a contig L50 of 1429. Our assembly pipeline also produced a single mitochondrial DNA contig of 14.00 kb. After polishing the genome, we identified 94.5% of single-copy gene orthologs from an Aves data set and 97.7% of single-copy gene orthologs from a vertebrata data set, which further demonstrates the high quality of our assembly. We anticipate that this genomic resource will be useful to the broader ornithological community and those interested in studying the evolutionary history and ecological interactions of larks, which comprise a widespread, yet understudied lineage of songbirds.

SGTK: a toolkit for visualization and assessment of scaffold graphs.

Scaffolding is an important step in every genome assembly pipeline, which allows to order contigs into longer sequences using various types of linkage information, such as mate-pair libraries and long reads. In this work, we operate with a notion of a scaffold graph-a graph, vertices of which correspond to the assembled contigs and edges represent connections between them. We present a software package called Scaffold Graph ToolKit that allows to construct and visualize scaffold graphs using different kinds of sequencing data. We show that the scaffold graph appears to be useful for analyzing and assessing genome assemblies, and demonstrate several use cases that can be helpful for both assembly software developers and their users. SGTK is implemented in C++, Python and JavaScript and is freely available at https://github.com/olga24912/SGTK. Supplementary data are available at Bioinformatics online.

Comparison of Highly and Weakly Virulent Dickeya solani Strains, With a View on the Pangenome and Panregulon of This Species.

Bacteria belonging to the genera Dickeya and Pectobacterium are responsible for significant economic losses in a wide variety of crops and ornamentals. During last years, increasing losses in potato production have been attributed to the appearance of Dickeya solani. The D. solani strains investigated so far share genetic homogeneity, although different virulence levels were observed among strains of various origins. The purpose of this study was to investigate the genetic traits possibly related to the diverse virulence levels by means of comparative genomics. First, we developed a new genome assembly pipeline which allowed us to complete the D. solani genomes. Four de novo sequenced and ten publicly available genomes were used to identify the structure of the D. solani pangenome, in which 74.8 and 25.2% of genes were grouped into the core and dispensable genome, respectively. For D. solani panregulon analysis, we performed a binding site prediction for four transcription factors, namely CRP, KdgR, PecS and Fur, to detect the regulons of these virulence regulators. Most of the D. solani potential virulence factors were predicted to belong to the accessory regulons of CRP, KdgR, and PecS. Thus, some differences in gene expression could exist between D. solani strains. The comparison between a highly and a low virulent strain, IFB0099 and IFB0223, respectively, disclosed only small differences between their genomes but significant differences in the production of virulence factors like pectinases, cellulases and proteases, and in their mobility. The D. solani strains also diverge in the number and size of prophages present in their genomes. Another relevant difference is the disruption of the adhesin gene fhaB2 in the highly virulent strain. Strain IFB0223, which has a complete adhesin gene, is less mobile and less aggressive than IFB0099. This suggests that in this case, mobility rather than adherence is needed in order to trigger disease symptoms. This study highlights the utility of comparative genomics in predicting D. solani traits involved in the aggressiveness of this emerging plant pathogen.

Abstract 4280: Improving the sensitivity of wide targeted cancer gene panels via novel genome analysis tools

Abstract In the recent years, wide targeted gene panels have gained popularity, due to their ability to interrogate many genes at the same time. In cancer, particularly, there is a set of ~600 genes known as Cancer Gene Census for which mutations have been causally implicated. Many of the wide cancer panels, therefore, target a subset of these genes. As targeted panels widen, the average coverage of them reduces, if the total budget of the DNA reads remains constant. Therefore, wide panels usually have a more modest coverage, as compared to narrow panels. The reduction in coverage, along with the biases that exist in targeted enrichment approaches make a challenging environment for genome assembly pipelines. We argue that, in such systems, false negatives are prone to increase to non-trivial values, primarily due to: 1) inefficiencies in the enrichment methods, especially if they are hybridization-based; 2) sporadic insufficiency of coverage; 3) biases in the analysis pipelines; 4) filtering operations that take place, in attempt to reduce false positives. As much of the losses are due to the dependency of the assays and the pipelines to the reference genome, we have approached this issue by designing a tandem set of tools: 1) A hybrid-denovo genome assembly pipeline, which has significantly less bias to the reference genome, as compared to the conventional align-to-reference methods. This pipeline can be used in lieu of or in combination with the conventional pipelines; 2) An in-silico verification (ISV) tool that provides the experts with a multifaceted visual and textual information, to gauge the evidence (or lack thereof) for the variants of interest. While not meant to necessarily be a replacement to wet validation, ISV provides the ability to identify the errors that may otherwise seep through the system. In order to show feasibility of this approach, a small set of FFPE TruSight Tumor 170 samples including cases of lung and breast cancer was used. The comparisons were done for all RefSeq exonic bases on a hereditary cancer gene subset. Our preliminary analysis using this data shows that by using our proprietary genome analysis pipeline and ISV tool, the sensitivity of the reported variants could be improved from ~80% to ~98% or higher, without impairing the specificity. If we consider intronic bases which have reasonable coverage, including those involved in splicing, the sensitivity improvements could be even larger. Citation Format: Bahram G. Kermani, Evans L. Roberts, Theresa A. Boyle, Anthony M. Magliocco. Improving the sensitivity of wide targeted cancer gene panels via novel genome analysis tools [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4280.

Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions.

Nanopore sequencing technology has the potential to render other sequencing technologies obsolete with its ability to generate long reads and provide portability. However, high error rates of the technology pose a challenge while generating accurate genome assemblies. The tools used for nanopore sequence analysis are of critical importance, as they should overcome the high error rates of the technology. Our goal in this work is to comprehensively analyze current publicly available tools for nanopore sequence analysis to understand their advantages, disadvantages and performance bottlenecks. It is important to understand where the current tools do not perform well to develop better tools. To this end, we (1) analyze the multiple steps and the associated tools in the genome assembly pipeline using nanopore sequence data, and (2) provide guidelines for determining the appropriate tools for each step. Based on our analyses, we make four key observations: (1) the choice of the tool for basecalling plays a critical role in overcoming the high error rates of nanopore sequencing technology. (2) Read-to-read overlap finding tools, GraphMap and Minimap, perform similarly in terms of accuracy. However, Minimap has a lower memory usage, and it is faster than GraphMap. (3) There is a trade-off between accuracy and performance when deciding on the appropriate tool for the assembly step. The fast but less accurate assembler Miniasm can be used for quick initial assembly, and further polishing can be applied on top of it to increase the accuracy, which leads to faster overall assembly. (4) The state-of-the-art polishing tool, Racon, generates high-quality consensus sequences while providing a significant speedup over another polishing tool, Nanopolish. We analyze various combinations of different tools and expose the trade-offs between accuracy, performance, memory usage and scalability. We conclude that our observations can guide researchers and practitioners in making conscious and effective choices for each step of the genome assembly pipeline using nanopore sequence data. Also, with the help of bottlenecks we have found, developers can improve the current tools or build new ones that are both accurate and fast, to overcome the high error rates of the nanopore sequencing technology.

GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes

BackgroundNext-generation sequencing (NGS) technologies have greatly promoted the genomic study of prokaryotes. However, highly fragmented assemblies due to short reads from NGS are still a limiting factor in gaining insights into the genome biology. Reference-assisted tools are promising in genome assembly, but tend to result in false assembly when the assigned reference has extensive rearrangements.ResultsHerein, we present GAAP, a genome assembly pipeline for scaffolding based on core-gene-defined Genome Organizational Framework (cGOF) described in our previous study. Instead of assigning references, we use the multiple-reference-derived cGOFs as indexes to assist in order and orientation of the scaffolds and build a skeleton structure, and then use read pairs to extend scaffolds, called local scaffolding, and distinguish between true and chimeric adjacencies in the scaffolds. In our performance tests using both empirical and simulated data of 15 genomes in six species with diverse genome size, complexity, and all three categories of cGOFs, GAAP outcompetes or achieves comparable results when compared to three other reference-assisted programs, AlignGraph, Ragout and MeDuSa.ConclusionsGAAP uses both cGOF and pair-end reads to create assemblies in genomic scale, and performs better than the currently available reference-assisted assembly tools as it recovers more assemblies and makes fewer false locations, especially for species with extensive rearranged genomes. Our method is a promising solution for reconstruction of genome sequence from short reads of NGS.

V-GAP: Viral genome assembly pipeline

Next-generation sequencing technologies have allowed the rapid determination of the complete genomes of many organisms. Although shotgun sequences from large genome organisms are still difficult to reconstruct perfect contigs each of which represents a full chromosome, those from small genomes have been assembled successfully into a very small number of contigs. In this study, we show that shotgun reads from phage genomes can be reconstructed into a single contig by controlling the number of read sequences used in de novo assembly. We have developed a pipeline to assemble small viral genomes with good reliability using a resampling method from shotgun data. This pipeline, named V-GAP (Viral Genome Assembly Pipeline), will contribute to the rapid genome typing of viruses, which are highly divergent, and thus will meet the increasing need for viral genome comparisons in metagenomic studies.

VirAmp: a galaxy-based viral genome assembly pipeline.

BackgroundAdvances in next generation sequencing make it possible to obtain high-coverage sequence data for large numbers of viral strains in a short time. However, since most bioinformatics tools are developed for command line use, the selection and accessibility of computational tools for genome assembly and variation analysis limits the ability of individual labs to perform further bioinformatics analysis.FindingsWe have developed a multi-step viral genome assembly pipeline named VirAmp, which combines existing tools and techniques and presents them to end users via a web-enabled Galaxy interface. Our pipeline allows users to assemble, analyze, and interpret high coverage viral sequencing data with an ease and efficiency that was not possible previously. Our software makes a large number of genome assembly and related tools available to life scientists and automates the currently recommended best practices into a single, easy to use interface. We tested our pipeline with three different datasets from human herpes simplex virus (HSV).ConclusionsVirAmp provides a user-friendly interface and a complete pipeline for viral genome analysis. We make our software available via an Amazon Elastic Cloud disk image that can be easily launched by anyone with an Amazon web service account. A fully functional demonstration instance of our system can be found at http://viramp.com/. We also maintain detailed documentation on each tool and methodology at http://docs.viramp.com.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-015-0060-y) contains supplementary material, which is available to authorized users.

MARAGAP: a modular approach to reference assisted genome assembly pipeline

This paper presents MARAGAP, a modular approach to reference assisted genome assembly pipeline. MARAGAP uses the principle of Minimum Description Length to determine the optimal reference sequence for the assembly. The optimal reference sequence is used as a template to infer inversions, insertions, deletions and SNPs in the target genome. MARAGAP uses an algorithmic approach to detect and correct inversions and deletions, a De-Bruijn graph based approach to infer the insertions, an affine-match affine-gap local alignment tool to estimate the locations of insertions and a Bayesian estimation framework for detecting SNPs.

GARM: Genome Assembly, Reconciliation and Merging Pipeline

Over the past decades DNA sequencing technologies have been improving in aspects like quality, read length, runtimes and yields, all at a lower cost. Despite these improvements, genome assembly remains a challenge in genome sequencing projects, especially when different sequencing platforms are used. At the present, there is no program that can handle and assemble different sequencing technologies better than specialized software for each of them. Also, very few protocols are available for merging results from different algorithms, technologies or both. We present GARM, (Genome Assembler, Reconciliation and Merging) a pipeline to merge assemblies from different algorithms or sequencing technologies.