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https://github.com/ruggleslab/rivet
Website source code for analysis of ribosome / polysome profiling
https://github.com/ruggleslab/rivet
polysome-profiling r ribosome-profiling shiny-apps website
Last synced: about 1 month ago
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Website source code for analysis of ribosome / polysome profiling
- Host: GitHub
- URL: https://github.com/ruggleslab/rivet
- Owner: ruggleslab
- Created: 2017-12-13T17:18:47.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-11-10T15:46:02.000Z (about 1 year ago)
- Last Synced: 2024-08-05T15:04:23.917Z (5 months ago)
- Topics: polysome-profiling, r, ribosome-profiling, shiny-apps, website
- Language: R
- Homepage:
- Size: 6.93 MB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-riboseq - Code - 018-5166-z) | Written in R; R Shiny app; Link defunct; EdgeR/Limma | (Differential Analysis)
README
# RIVET (Ribosomal Investigation and Visualization to Evaluate Translation)
RIVET is a simple to use R-shiny based graphical user interface to automate the statistical analysis of RNA sequencing data and microarray data generated by either polysome profiling or ribosome footprinting. RIVET requires a tab-delimited or comma-delimited text file of counts data (commonly generated in many RNA seq computational pipelines) or background corrected and normalized microarray data. The main goal of RIVET is to make data analysis of data generated by genome-wide translatome experiments accessible to bench scientists.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
* R
* shiny
* limma
* Biobase
* ggplot2
* edgeR
* gplots
* RColorBrewer
* shinythemes
* shinyjs
### Deployment
For local deployment, all app files including ui.R, server.R, global.R along with www folder should be located within the working directory. To launch from the commandline, open a terminal and begin an R session within the working directory.
To install required packages, start R and enter:
```
# for cran packages
>install.packages('shiny')
>install.packages('ggplot2')
>install.packages('gplots')
>install.packages('RColorBrewer')
>install.packages('shinythemes')
>install.packages('shinyjs')
# for bioconductor packages
>source("https://bioconductor.org/biocLite.R")
>biocLite('limma')
>biocLite('edgeR')
>biocLite('Biobase')
```
To launch the RIVET app locally, execute the following in terminal (while not in R session) where ~/shinyapp should be replaced with the path to your application:
```
Rscript -e 'library(methods); shiny::runApp("~/shinyapp", launch.browser=TRUE)'
```
Alternatively, you can open any of the rivet "*.R" files in an R IDE and select "Run App" from the top command bar.
## Built With
* [R shiny](https://shiny.rstudio.com) - The web framework used
## Example Use and Citations
For example RIVET use cases and citations please refer to the Wiki.
## Authors
* **Amanda Ernlund** - *Initial work*
* **Kelly Ruggles** - *Maintainer*
## License
This project will be licensed soon.
## Acknowledgments
* Hat tip to:
- Cooper for code advice
- Dr. Robert Schneider for scientific interpretation