Microarray and Machine Learning 📊🤖

This repository is a comprehensive resource for learning microarray analysis and machine learning using R. It provides step-by-step analytical workflows, covering data preprocessing, feature selection, dimensionality reduction, and predictive modeling.

Key Focus:

🔹 Microarray Data Analysis – Processing and analyzing high-dimensional microarray datasets.

🔹 Machine Learning in R – Applying PCA, feature selection, and classification for pattern discovery.

🔹 Reproducible Research – Providing well-documented R scripts for transparent and reproducible analysis.

🧬 Dataset Description

We are using a publicly available gastric cancer microarray dataset from NCBI GEO (Gene Expression Omnibus). Assession Id: GSE79973

You can access the normalized dataset directly from this repository:📁Microarray_Series_R/gastric_cancer.csv

📌 Topics Covered So Far:

• Microarray Data Analysis Overview in R
  R script || Tutorial

• PCA for Microarray Data in R
  R script || Tutorial

• Stepwise Logistic Regression in R
  R script. || Tutorial

• Recursive Features Elimination (RFE)
  R Script || Tutorial

• Boruta Feature Sekection
  R script || Tutorial

More tutorials and workflows coming soon! Stay tuned for updates. 🚀