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      MinION Analysis and Reference Consortium: Phase 2 data release and analysis of R9.0 chemistry

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          Abstract

          Background: Long-read sequencing is rapidly evolving and reshaping the suite of opportunities for genomic analysis. For the MinION in particular, as both the platform and chemistry develop, the user community requires reference data to set performance expectations and maximally exploit third-generation sequencing. We performed an analysis of MinION data derived from whole genome sequencing of Escherichia coli K-12 using the R9.0 chemistry, comparing the results with the older R7.3 chemistry.

          Methods: We computed the error-rate estimates for insertions, deletions, and mismatches in MinION reads.

          Results: Run-time characteristics of the flow cell and run scripts for R9.0 were similar to those observed for R7.3 chemistry, but with an 8-fold increase in bases per second (from 30 bps in R7.3 and SQK-MAP005 library preparation, to 250 bps in R9.0) processed by individual nanopores, and less drop-off in yield over time. The 2-dimensional (“2D”) N50 read length was unchanged from the prior chemistry. Using the proportion of alignable reads as a measure of base-call accuracy, 99.9% of “pass” template reads from 1-dimensional (“1D”)  experiments were mappable and ~97% from 2D experiments. The median identity of reads was ~89% for 1D and ~94% for 2D experiments. The total error rate (miscall + insertion + deletion ) decreased for 2D “pass” reads from 9.1% in R7.3 to 7.5% in R9.0 and for template “pass” reads from 26.7% in R7.3 to 14.5% in R9.0.

          Conclusions: These Phase 2 MinION experiments serve as a baseline by providing estimates for read quality, throughput, and mappability. The datasets further enable the development of bioinformatic tools tailored to the new R9.0 chemistry and the design of novel biological applications for this technology.

          Abbreviations: K: thousand, Kb: kilobase (one thousand base pairs), M: million, Mb: megabase (one million base pairs), Gb: gigabase (one billion base pairs).

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          Improved data analysis for the MinION nanopore sequencer

          The Oxford Nanopore MinION sequences individual DNA molecules using an array of pores that read nucleotide identities based on ionic current steps. We evaluated and optimized MinION performance using M13 genomic dsDNA. Using expectation-maximization (EM) we obtained robust maximum likelihood (ML) estimates for read insertion, deletion and substitution error rates (4.9%, 7.8%, and 5.1% respectively). We found that 99% of high-quality ‘2D’ MinION reads mapped to reference at a mean identity of 85%. We present a MinION-tailored tool for single nucleotide variant (SNV) detection that uses ML parameter estimates and marginalization over many possible read alignments to achieve precision and recall of up to 99%. By pairing our high-confidence alignment strategy with long MinION reads, we resolved the copy number for a cancer/testis gene family (CT47) within an unresolved region of human chromosome Xq24.
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            Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM

            Heng Li (2013)
            Summary: BWA-MEM is a new alignment algorithm for aligning sequence reads or long query sequences against a large reference genome such as human. It automatically chooses between local and end-to-end alignments, supports paired-end reads and performs chimeric alignment. The algorithm is robust to sequencing errors and applicable to a wide range of sequence lengths from 70bp to a few megabases. For mapping 100bp sequences, BWA-MEM shows better performance than several state-of-art read aligners to date. Availability and implementation: BWA-MEM is implemented as a component of BWA, which is available at http://github.com/lh3/bwa. Contact: hengli@broadinstitute.org
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              A reference bacterial genome dataset generated on the MinION™ portable single-molecule nanopore sequencer

              Background The MinION™ is a new, portable single-molecule sequencer developed by Oxford Nanopore Technologies. It measures four inches in length and is powered from the USB 3.0 port of a laptop computer. The MinION™ measures the change in current resulting from DNA strands interacting with a charged protein nanopore. These measurements can then be used to deduce the underlying nucleotide sequence. Findings We present a read dataset from whole-genome shotgun sequencing of the model organism Escherichia coli K-12 substr. MG1655 generated on a MinION™ device during the early-access MinION™ Access Program (MAP). Sequencing runs of the MinION™ are presented, one generated using R7 chemistry (released in July 2014) and one using R7.3 (released in September 2014). Conclusions Base-called sequence data are provided to demonstrate the nature of data produced by the MinION™ platform and to encourage the development of customised methods for alignment, consensus and variant calling, de novo assembly and scaffolding. FAST5 files containing event data within the HDF5 container format are provided to assist with the development of improved base-calling methods.
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                Author and article information

                Journal
                F1000Res
                F1000Res
                F1000Research
                F1000Research
                F1000Research (London, UK )
                2046-1402
                31 May 2017
                2017
                : 6
                : 760
                Affiliations
                [1 ]University of California at Santa Cruz, Santa Cruz, CA, USA
                [2 ]Michael Smith Laboratories and Djavad Mowfaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
                [3 ]School of Life Sciences, University of Nottingham, Nottingham, UK
                [4 ]Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
                [5 ]Peter Medawar Building for Pathogen Research, University of Oxford, Oxford, UK
                [6 ]Malaghan Institute of Medical Research, Wellington, New Zealand
                [7 ]Norwich Medical School, University of East Anglia, Norwich, UK
                [8 ]Earlham Institute, Norwich Research Park, Norwich, UK
                [9 ]Science for Life Laboratory, IGP, Uppsala University, Uppsala, Sweden
                [10 ]ZF-screens B.V., Leiden, Netherlands
                [11 ]European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK
                [12 ]Virginia Commonwealth University, Richmond, VA, USA
                [1 ]Department of Population Health and Reproduction, University of California, Davis, Davis, CA, USA
                [2 ]Department of Population Health and Reproduction, University of California, Davis, CA, USA
                [1 ]Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan
                [2 ]Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
                [3 ]Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan
                [1 ]Department of Genetics, University Medical Center Utrecht, Utrecht, Netherlands
                Author notes

                * Equal contributors

                MJ and JT coordinated the study. The MARC group collectively designed the study. ML, SM, and JT performed the experiments. VZ, RL, ML, MJ, RL and CI ran data pre-processing steps. MJ, CI and JT analysed the data. MJ and BB drafted the manuscript. All authors participated in discussions relating to the generation and analysis of the data and edited and approved the final manuscript for submission.

                Competing interests: All flow cells and library preparation kits were provided by ONT free of charge. Ewan Birney is a paid consultant of ONT. MJ, HEO, JT, ML, CI, HJ, JOG and BB have accepted reimbursement for conference travel expenses from ONT. VZ was funded for his work on this project from Oxford Nanopore through an agreement with EMBL.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Author information
                https://orcid.org/0000-0002-4571-3982
                https://orcid.org/0000-0003-4634-4995
                https://orcid.org/0000-0003-3044-4297
                https://orcid.org/0000-0002-8563-4146
                https://orcid.org/0000-0002-7722-1958
                Article
                10.12688/f1000research.11354.1
                5538040
                28794860
                aea9bd61-ebc4-4d08-afb7-36bf57945c3f
                Copyright: © 2017 Jain M et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 May 2017
                Funding
                Funded by: National Human Genome Research Institute
                Award ID: HG007827
                Funded by: The Michael Smith Foundation for Health Research and the Koerner Foundation
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/J010375/1
                Funded by: National Science Foundation
                Award ID: DEB-1355059
                Funded by: National Human Genome Research Institute
                Award ID: HG006321
                Funded by: Canadian Institutes of Health Research
                Award ID: 10677
                Funded by: Brain Canada Multi-Investigator Research Initiative Grant with matching support from Genome British Columbia
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/M020061/1
                Funded by: Wellcome Trust
                Award ID: 090532/Z/09/Z
                Funded by: UK Antimicrobial Resistance Cross Council Initiative
                Award ID: MR/N013956/1
                Funded by: Rosetrees Trust
                Award ID: A749
                Funded by: E o R Börjessons Foundation
                The following grants supported the research of the following authors: NHGRI, USA award numbers HG006321 and HG007827 (MJ and HEO, UCSC), Canadian Institutes of Health Research #10677 (JT and TS, UBC), Brain Canada Multi-Investigator Research Initiative Grant with matching support from Genome British Columbia, the Michael Smith Foundation for Health Research and the Koerner Foundation (JT and TS, UBC), BBSRC grant BB/M020061/1 (ML and SM, Nottingham), Wellcome Trust grant 090532/Z/09/Z (CI, WTCHG), UK Antimicrobial Resistance Cross Council Initiative supported by the seven research councils (MR/N013956/1) and Rosetrees Trust grant A749 (JOG, UEA), BBSRC grant BB/J010375/1 (RML, Earlham), E o R Börjessons foundation (OW, Uppsala), and National Science Foundation DEB-1355059 (BB, VCU).
                Categories
                Research Article
                Articles
                Genomics

                minion,nanopore sequencing,r9 chemistry,csgg,data release,long reads,minotour,marginalign,nanook,third-generation sequencing

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