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Báo cáo y học: "Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. | Goecks et al. Genome Biology 2010 11 R86 http genomebiology.eom 2010 11 8 R86 Genome Biology SOFTWARE Open Access Galaxy a comprehensive approach for supporting accessible reproducible and transparent computational research in the life sciences Jeremy Goecks1 Anton Nekrutenko2 James Taylor1 The Galaxy Team Abstract 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. Rationale Computation has become an essential tool in life science research. This is exemplified in genomics where first microarrays and now massively parallel DNA sequencing have enabled a variety of genome-wide functional assays such as ChIP-seq 1 and RNA-seq 2 and many others that require increasingly complex analysis tools 3 . However sudden reliance on computation has created an informatics crisis for life science researchers computational resources can be difficult to use and ensuring that computational experiments are communicated well and hence reproducible is challenging. Galaxy helps to address this crisis by providing an open webbased platform for performing accessible reproducible and transparent genomic science. The problem of accessibility of computational tools has long been recognized. Without programming or informatics expertise scientists needing to use computational approaches are impeded by problems ranging from tool installation to determining which parameter values to use to efficiently combining multiple tools together in an analysis chain. The severity of these problems is evidenced by the .