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      The reconstruction of 2,631 draft metagenome-assembled genomes from the global oceans

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          Abstract

          Microorganisms play a crucial role in mediating global biogeochemical cycles in the marine environment. By reconstructing the genomes of environmental organisms through metagenomics, researchers are able to study the metabolic potential of Bacteria and Archaea that are resistant to isolation in the laboratory. Utilizing the large metagenomic dataset generated from 234 samples collected during the Tara Oceans circumnavigation expedition, we were able to assemble 102 billion paired-end reads into 562 million contigs, which in turn were co-assembled and consolidated in to 7.2 million contigs ≥2 kb in length. Approximately 1 million of these contigs were binned to reconstruct draft genomes. In total, 2,631 draft genomes with an estimated completion of ≥50% were generated (1,491 draft genomes >70% complete; 603 genomes >90% complete). A majority of the draft genomes were manually assigned phylogeny based on sets of concatenated phylogenetic marker genes and/or 16S rRNA gene sequences. The draft genomes are now publically available for the research community at-large.

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          Most cited references 45

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

           Robert Edgar (2004)
          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                16 January 2018
                2018
                : 5
                Affiliations
                [1 ]Center for Dark Energy Biosphere Investigations, University of Southern California , Los Angeles, CA 90089, USA
                [2 ]Department of Biological Sciences, University of Southern California , Los Angeles, CA 90089, USA
                Author notes
                [a ] B.J.T. (email: tully.bj@ 123456gmail.com ).
                []

                B.J.T. conceived of and designed the methodology, performed the analysis, wrote the paper, and prepared the figure and tables. E.D.G. performed the analysis and reviewed drafts of the paper. J.H.F. provided funding and resources to perform the analysis and reviewed drafts of the paper.

                Article
                sdata2017203
                10.1038/sdata.2017.203
                5769542
                29337314
                Copyright © 2018, The Author(s)

                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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.

                Categories
                Data Descriptor

                bioinformatics, genome, metagenomics, water microbiology

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