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Michaela Spitzer, Juri Rappsilber, Mike Tyers (Wellcome Trust Centre for Cell Biology, Edinburgh, UK; IRIC, Montreal, Canada)
The R-package 'shiny', released by RStudio in November 2012, has the potential to take the analysis of biological data to a new level. ‘shiny’ enables programmers to quickly convert their R-code into an application, which allows biologists to explore and manipulate their data interactively. There are multiple options to enter input parameters for data analysis and visualisation to a ‘shiny’ application. Furthermore, tabsets allow the implementation of different types of visualization styles for a given data set, some of which may assist the biologist by presenting different parameter choices. This provides flexibility and independence for biologists to truly explore their data while freeing the programmer from the burden of generating plots with different parameters and from repetitive analysis of different data sets. We present two examples of ‘shiny’ applications that proved very useful and efficient: i) 96 well-based growth curve data analysis and ii) visualization and assessment of results from open modification searches of proteomic mass spectra.