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      De novo Assembly of the Brugia malayi Genome Using Long Reads from a Single MinION Flowcell

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          Abstract

          Filarial nematode infections cause a substantial global disease burden. Genomic studies of filarial worms can improve our understanding of their biology and epidemiology. However, genomic information from field isolates is limited and available reference genomes are often discontinuous. Single molecule sequencing technologies can reduce the cost of genome sequencing and long reads produced from these devices can improve the contiguity and completeness of genome assemblies. In addition, these new technologies can make generation and analysis of large numbers of field isolates feasible. In this study, we assessed the performance of the Oxford Nanopore Technologies MinION for sequencing and assembling the genome of Brugia malayi, a human parasite widely used in filariasis research. Using data from a single MinION flowcell, a 90.3 Mb nuclear genome was assembled into 202 contigs with an N50 of 2.4 Mb. This assembly covered 96.9% of the well-defined B. malayi reference genome with 99.2% identity. The complete mitochondrial genome was obtained with individual reads and the nearly complete genome of the endosymbiotic bacteria Wolbachia was assembled alongside the nuclear genome. Long-read data from the MinION produced an assembly that approached the quality of a well-established reference genome using comparably fewer resources.

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          Most cited references 34

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                fauverjoseph@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                20 December 2019
                20 December 2019
                2019
                : 9
                Affiliations
                [1 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, ; St. Louis, MO United States
                [2 ]ISNI 0000 0001 2355 7002, GRID grid.4367.6, McDonnell Genome Institute, Washington University School of Medicine, ; St. Louis, MO United States
                [3 ]ISNI 0000000419368710, GRID grid.47100.32, Present Address: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, ; New Haven, CT United States
                Article
                55908
                10.1038/s41598-019-55908-y
                6925183
                31863009
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                dna sequencing, medical genomics

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