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      Ten simple rules for making research software more robust

      1 , * , 2

      PLoS Computational Biology

      Public Library of Science

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Software produced for research, published and otherwise, suffers from a number of common problems that make it difficult or impossible to run outside the original institution or even off the primary developer’s computer. We present ten simple rules to make such software robust enough to be run by anyone, anywhere, and thereby delight your users and collaborators.

          Author summary

          Many researchers have found out the hard way that there’s a world of difference between “works for me on my machine” and “works for other people on theirs.” Many common challenges can be avoided by following a few simple rules; doing so not only improves reproducibility but can accelerate research.

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          Most cited references 20

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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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            The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update

            High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.
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              1,500 scientists lift the lid on reproducibility.

               Monya Baker (2016)
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                Author and article information

                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                April 2017
                13 April 2017
                : 13
                : 4
                Affiliations
                [1 ]Genome Sequence Informatics, Ontario Institute for Cancer Research, Toronto, Ontario, Canada
                [2 ]Software Carpentry Foundation, Austin, Texas, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Article
                PCOMPBIOL-D-16-01683
                10.1371/journal.pcbi.1005412
                5390961
                28407023
                © 2017 Taschuk, Wilson

                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.

                Page count
                Figures: 0, Tables: 0, Pages: 10
                Product
                Funding
                This work was partially funded by the Ontario Institute for Cancer Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Editorial
                Computer and Information Sciences
                Computer Software
                Computer and Information Sciences
                Software Engineering
                Software Development
                Engineering and Technology
                Software Engineering
                Software Development
                Computer and Information Sciences
                Software Engineering
                Software Tools
                Engineering and Technology
                Software Engineering
                Software Tools
                Computer and Information Sciences
                Software Engineering
                Engineering and Technology
                Software Engineering
                Research and Analysis Methods
                Research Assessment
                Reproducibility
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                Computer and Information Sciences
                Operating Systems

                Quantitative & Systems biology

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