VS Code for Clinical & Biological Data Analysis with R

A Hands-On Workshop for Non-Developers

Welcome! This tutorial will guide you through using Visual Studio Code (VS Code) with AI assistance to analyze clinical and biological data. By the end, you'll be able to independently analyze your own datasets using R.

🎯 Workshop Goals

• Set up VS Code for R data analysis
• Learn to use GitHub Copilot AI assistant effectively
• Develop a systematic approach to data analysis
• Analyze the ovarian cancer dataset step-by-step
• Become independent in your data analysis workflow

📚 Tutorial Structure

00 - Prerequisites

✅ Installation checklist
✅ GitHub account setup for Copilot
✅ VS Code and R configuration

01 - Getting Started with VS Code

🖥️ Understanding the VS Code interface
🔧 Essential features and shortcuts
💡 First steps with R in VS Code

02 - AI Assistant Modes

�� Understanding Copilot modes: Chat, Edit, Agent
💬 How to ask effective questions
✨ Hands-on practice with each mode

03 - Data Analysis Workflow

📊 The systematic approach to analyzing data
🧬 Ovarian cancer dataset walkthrough
📈 From data exploration to visualization
✅ Quality control and verification

04 - Best Practices

✓ Verification checklist
⚠️ Common pitfalls to avoid
🎯 How to work effectively with AI

05 - Resources & Next Steps

🔧 Troubleshooting guide
📖 Where to go from here
📝 Templates for your own projects

🗂️ Dataset

We'll use a simulated ovarian cancer dataset with:

• Treatment (0 = no treatment, 1 = treatment)
• HighRisk (0 = low risk, 1 = high risk)
• Time (survival time in months)
• Status (0 = censored, 1 = event occurred)

Source: Cancer Informatics

🚀 Quick Start

1. Before the workshop: Complete 00-prerequisites
2. During the workshop: Follow along section by section
3. After the workshop: Use the templates for your own data

📝 Workshop Timeline

Time	Section	Activity
0:00-0:30	Setup & Introduction	Prerequisites check, VS Code orientation
0:30-1:00	AI Assistant	Understanding and practicing with Copilot modes
1:00-2:30	Data Analysis	Guided ovarian dataset analysis
2:30-2:50	Best Practices	Verification, quality control, tips
2:50-3:00	Wrap-up	Q&A, next steps, templates

🆘 Need Help?

During the workshop, raise your hand or use the chat. After the workshop, refer to the troubleshooting guide.

📌 Important Notes

• This is a judgment-free zone - everyone learns at their own pace
• Mistakes are learning opportunities - the AI is here to help
• Ask questions - if you're confused, others probably are too
• Focus on the process, not memorization - you'll have these materials to reference

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Let's get started! → Go to Prerequisites