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      Galaxy tools and workflows for sequence analysis with applications in molecular plant pathology

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          Abstract

          The Galaxy Project offers the popular web browser-based platform Galaxy for running bioinformatics tools and constructing simple workflows. Here, we present a broad collection of additional Galaxy tools for large scale analysis of gene and protein sequences. The motivating research theme is the identification of specific genes of interest in a range of non-model organisms, and our central example is the identification and prediction of “effector” proteins produced by plant pathogens in order to manipulate their host plant. This functional annotation of a pathogen’s predicted capacity for virulence is a key step in translating sequence data into potential applications in plant pathology.

          This collection includes novel tools, and widely-used third-party tools such as NCBI BLAST+ wrapped for use within Galaxy. Individual bioinformatics software tools are typically available separately as standalone packages, or in online browser-based form. The Galaxy framework enables the user to combine these and other tools to automate organism scale analyses as workflows, without demanding familiarity with command line tools and scripting. Workflows created using Galaxy can be saved and are reusable, so may be distributed within and between research groups, facilitating the construction of a set of standardised, reusable bioinformatic protocols.

          The Galaxy tools and workflows described in this manuscript are open source and freely available from the Galaxy Tool Shed ( http://usegalaxy.org/toolshed or http://toolshed.g2.bx.psu.edu).

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          Most cited references38

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            The Bioperl toolkit: Perl modules for the life sciences.

            The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.
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              Fungal effector proteins.

              It is accepted that most fungal avirulence genes encode virulence factors that are called effectors. Most fungal effectors are secreted, cysteine-rich proteins, and a role in virulence has been shown for a few of them, including Avr2 and Avr4 of Cladosporium fulvum, which inhibit plant cysteine proteases and protect chitin in fungal cell walls against plant chitinases, respectively. In resistant plants, effectors are directly or indirectly recognized by cognate resistance proteins that reside either inside the plant cell or on plasma membranes. Several secreted effectors function inside the host cell, but the uptake mechanism is not yet known. Variation observed among fungal effectors shows two types of selection that appear to relate to whether they interact directly or indirectly with their cognate resistance proteins. Direct interactions seem to favor point mutations in effector genes, leading to amino acid substitutions, whereas indirect interactions seem to favor jettison of effector genes.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                17 September 2013
                2013
                : 1
                : e167
                Affiliations
                [1 ]Information and Computational Sciences, James Hutton Institute , UK
                [2 ]Pharmaceutical Bioinformatics, Institute of Pharmaceutical Sciences, Albert-Ludwigs-University , Freiburg, Germany
                [3 ]Wellcome Trust Biomedical Informatics Hub and Exeter Sequencing Service, University of Exeter , UK
                Article
                167
                10.7717/peerj.167
                3792188
                24109552
                9123b4e6-dfb4-4df4-b08b-e5fa8e942050
                © 2013 Cock et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 17 July 2013
                : 30 August 2013
                Funding
                Funded by: Scottish Government Rural and Environmental Research and Analysis Directorate
                Funded by: Excellence Initiative of the German Federal and State Governments through the Junior Research Group Program (ZUK 43)
                PJC and LP are supported by the Scottish Government Rural and Environmental Research and Analysis Directorate. The work from BAG has been funded by the Excellence Initiative of the German Federal and State Governments through the Junior Research Group Program (ZUK 43). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Agricultural Science
                Bioinformatics
                Computational Biology
                Genomics
                Molecular Biology

                galaxy,pipeline,accessibility,effector proteins,workflow,reproducibility,annotation,sequence analysis,genomics

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