OmicsInsight

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Biomarker Discovery Workshop: Unraveling Insights from Omics Data

Welcome to the Biomarker Discovery Workshop! In this repository, we explore the fascinating world of biomarkers using omics data. Whether you're a researcher, a data enthusiast, or simply curious about the intersection of biology and data science, this workshop provides valuable insights.

Overview

• Objective: Our goal is to identify potential biomarkers (genes, proteins, metabolites) associated with different subtypes of glioblastoma multiforme (GBM), a highly aggressive brain tumor.
• Dataset: We'll work with mRNA expression measurements from GBM tumors, which were previously published in Cancer Cell.
• Approach: We'll follow a data-driven pipeline, combining visualization, machine learning, and variable selection techniques.

Workshop Steps

1. Data Input and Visualization:

   • Load the provided data.
   • Create essential visualizations to understand the dataset.

2. Data Splitting:

   • Divide the data into train and test sets.
   • Ensure robust model evaluation.

3. Random Forest Model:

   • Fit a basic random forest model using all training data.
   • Evaluate its performance on the test data.

4. Variable Selection Rounds:

   • Iteratively refine our biomarker candidates.
   • Use cross-validation to select informative features.

5. Reduced Variable Model:

   • Build a focused model with a reduced set of variables.
   • Assess its performance.

6. Practice and Exploration:

   • Deepen your understanding through practice.

Getting Started

1. Prerequisites:

   • Install R and RStudio.
   • Download the provided dataset files: GlioblastomaExpressionData_Practical2.csv and GlioblastomaMetadata_Practical2.csv.

2. Folder Structure:

   • Save the downloaded files in your desired directory.
   • Set your working directory to this folder in RStudio.

3. Start Coding:

   • Open a new script in RStudio.
   • Save it in your chosen folder.
   • Begin your exploration!

Acknowledgments

This workshop material is based on the original dataset published in Cancer Cell. We appreciate the contributions of the research community and the UK Biobank for making valuable data available.

Feel free to explore, learn, and contribute. Happy biomarker hunting! 🧬🔍🌟

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Feel free to customize this readme to suit your specific context and repository. Best of luck with your biomarker discovery journey! 🚀