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R Studio Server v0.1beta

The server is set up to assist with statistical analyses on medical data.

I. Access to R Server

You can't access R Studio here

Server is offline

II. Request Access

If you'd like to request R Studio acces, please fill out the form below

III. Documentation

R Studio Server Guide

Welcome to the R Studio Server! This document explains how to access and use the R Studio server for your data analysis and statistical needs.

1. Accessing the Server

To access the R Studio server, follow these steps:

  1. Open your web browser and navigate to the following link:
  2. R Studio Server
  3. You will be directed to the login page (if required).

Note: You must have an account and login credentials to access the server. If you don't have access, please use the aforementioned request form.

2. Login and Authentication

  1. Enter your username and password.
  2. Click on Sign In.
  3. If your login is successful, you will be redirected to the R Studio interface.

Tip: If you forgot your password, please contact support.

3. Navigating the Interface

Once logged in, you'll see the R Studio interface split into four main panels:

Main Panels:

  1. Source Panel (top-left): This is where you write and edit R scripts.
  2. Console Panel (bottom-left): The interactive console where you can run R commands.
  3. Environment/History Panel (top-right): View data objects, variables, and command history.
  4. Files/Plots/Packages/Help Panel (bottom-right): Manage files, view plots, manage packages, and access help resources.

Writing and Running Code

  • To run a line of code or a script:
  • Write your R code in the Source panel.
  • Press Ctrl + Enter (Windows/Linux) or Cmd + Enter (Mac) to run the current line or selection.
  • Check the Console panel for output and any error messages.

4. Working with Projects

Creating and managing projects in R Studio helps organize your work:

  1. To create a new project:
  2. Go to File -> New Project.
  3. Choose whether to create a project from a new directory, an existing directory, or a Git repository.
  4. Name the project and select its directory.
  5. Click Create Project to open the new project in R Studio.

5. Installing Packages

You can install R packages to extend the functionality of R Studio:

  1. In the Console panel, type the following command to install a package: r install.packages("package_name")
  2. To load a package into your environment, use: r library(package_name)
  3. You can also install packages from the Packages tab in the bottom-right panel by searching for the package name and clicking Install.

6. Uploading and Managing Data

You can upload datasets directly to the R Studio server:

  1. In the Files tab (bottom-right), click on Upload.
  2. Choose the file you want to upload from your local machine.
  3. The uploaded file will now appear in your file system and can be accessed in your R scripts.

To read a CSV file into R, use:

data <- read.csv("your_file.csv")

7. Saving and Exporting Results

  • To save your R script, go to File -> Save As, and choose the directory.
  • To export a plot:
  • Go to the Plots panel.
  • Click Export and choose to save the plot as a PDF, PNG, or other formats.

8. Best Practices

  • Project organization: Always create a new project for each analysis to avoid clutter.
  • Save your work frequently: Make sure to save scripts and data regularly.
  • Version control: Use Git for version control to track changes to your scripts.

9. Troubleshooting

Common Issues

  • Package not installing: Check the console for error messages. It may be due to missing dependencies.
  • Slow performance: Large datasets or heavy computations may slow down the server. Try to simplify your code or break tasks into smaller parts.

10. Support and Contact

If you are encountering issues, feel free to contact us.

This concludes the guide to using the R Studio server. We hope this document helps you get the most out of the platform!