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# **i2dash**: - **I**nteractive & **i**terative **dash**boards in R <img src="vignettes/images/i2dash_logo.png" align="right" width="150px"/>
# Interactive & iterative dashboards in R
## Abstract
## Abstract <img src="vignettes/images/i2dash_logo.png" align="right" width="150px" />
Scientific communication and data visualization are important aspects to illustrate complex concepts and results from data analyses. The R package **i2dash** provides functionality to create customized, web-based dashboards for data presentation, exploration and sharing. **i2dash** integrates easily into existing data analysis pipelines and can organize scientific findings thematically across different pages and layouts.
### Main features
- Easy integration into existing analysis pipelines in R
- Support for multiple components, such as htmlwidgets, tabular data, text, images etc.
- Easy integration into existing analysis pipelines in R for programmatic dashboard creation
- Provides a selection of predefined layouts to arrange content
- Support for multiple components, such as htmlwidgets, tables, text, images etc.
- Creation of web-based, sharable, static or interactive dashboards
- Enables a flexible and iterative cycle of dashboard development
![](man/figures/i2dash_image.jpg)
![](vignettes/images/i2dash_intro.png)
*A customized dashboard can be integrated into an existing data analysis pipelines in R (left). After initialization, pages containing components with customized content can be added step-by-step to the dashboard at any stage of the data analysis. The final dashboard is assembled into an R markdown file, and shared together with RDS data files for further use within RStudio, or can also be deployed on a R Shiny Server or as stand-alone HTML file.*
*(A) dashboard is initialized at the beginning of a data analysis pipeline. During the pipeline run, new content, results, or data visualizations are iteratively added to the dashboard’s pages. The final dashboard is rendered into a static or interactive document. (B) Pages added to the dashboard can be arranged in a flexible manner from a selection of predefined layouts. (C) Examples of programmatically created dashboards. (D) The i2dash docker container, providing all dependencies for interactive, shiny based apps, can be used to easily deploy individual data interpretations on a cloud infrastructure, such as Kubernetes, as a micro service.*
## Installation:
## Installation
The package can be installed with the `r BiocStyle::CRANpkg("remotes")` library:
The package can be installed with:
```{r, eval=FALSE}
remotes::install_git(url = "https://gitlab.gwdg.de/loosolab/software/i2dash.git", repos = BiocManager::repositories())
```
install.packages("i2dash")
```
## Where to start
......@@ -36,7 +36,9 @@ It is possible to extend the core functionality of **i2dash** with templates for
## How to cite
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If you use **i2dash** or **i2dash.scrnaseq** in your work, please cite:
Ustjanzew A., Preussner J., Bentsen M., Kuenne C., and Looso M. i2dash: creation of flexible, interactive and web-based dashboards from data analysis pipelines. *tba* (2020)
## License
......
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<pre>MIT License
Copyright (c) 2019 Mario Looso, Jens Preussner and Arsenij Ustjanzew
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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