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      ReadXplorer—visualization and analysis of mapped sequences

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          Abstract

          Motivation: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data.

          Results: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion–insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets.

          Availability and implementation: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual.

          Contact: rhilker@ 123456mikrobio.med.uni-giessen.de

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references22

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          Vienna RNA secondary structure server.

          The Vienna RNA secondary structure server provides a web interface to the most frequently used functions of the Vienna RNA software package for the analysis of RNA secondary structures. It currently offers prediction of secondary structure from a single sequence, prediction of the consensus secondary structure for a set of aligned sequences and the design of sequences that will fold into a predefined structure. All three services can be accessed via the Vienna RNA web server at http://rna.tbi.univie.ac.at/.
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            An integrated semiconductor device enabling non-optical genome sequencing.

            The seminal importance of DNA sequencing to the life sciences, biotechnology and medicine has driven the search for more scalable and lower-cost solutions. Here we describe a DNA sequencing technology in which scalable, low-cost semiconductor manufacturing techniques are used to make an integrated circuit able to directly perform non-optical DNA sequencing of genomes. Sequence data are obtained by directly sensing the ions produced by template-directed DNA polymerase synthesis using all-natural nucleotides on this massively parallel semiconductor-sensing device or ion chip. The ion chip contains ion-sensitive, field-effect transistor-based sensors in perfect register with 1.2 million wells, which provide confinement and allow parallel, simultaneous detection of independent sequencing reactions. Use of the most widely used technology for constructing integrated circuits, the complementary metal-oxide semiconductor (CMOS) process, allows for low-cost, large-scale production and scaling of the device to higher densities and larger array sizes. We show the performance of the system by sequencing three bacterial genomes, its robustness and scalability by producing ion chips with up to 10 times as many sensors and sequencing a human genome.
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              Fast folding and comparison of RNA secondary structures

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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 August 2014
                30 April 2014
                30 April 2014
                : 30
                : 16
                : 2247-2254
                Affiliations
                1Institute of Medical Microbiology, Justus-Liebig-University, 35392 Giessen, Germany, 2Faculty of Biology, 3Institute for Bioinformatics, Center for Biotechnology, 4Computational Genomics, Center for Biotechnology, 5Technology Platform Genomics, Center for Biotechnology, 6Genome Informatics, Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany and 7Bioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, 35392 Giessen, Germany
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Michael Brudno

                Article
                btu205
                10.1093/bioinformatics/btu205
                4217279
                24790157
                5282978e-000c-45fb-ad78-dd217a44759a
                © The Author 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 November 2013
                : 27 March 2014
                : 16 April 2014
                Page count
                Pages: 8
                Categories
                Original Papers
                Genome Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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