A comprehensive toolkit for analyzing gene expression data, including preprocessing, clustering, differential expression analysis, and functional annotation. GeneExpressionAnalysis is a comprehensive toolkit designed for analyzing gene expression data. This repository provides scripts for:
- Data Preprocessing: Handling missing values and standardizing data.
- Clustering Analysis: Using K-means and hierarchical clustering to identify natural groupings in the data.
- Differential Expression Analysis: Identifying significantly differentially expressed genes between groups.
- Visualization: Creating PCA plots, volcano plots, and heatmaps to visualize analysis results.
- Functional Annotation and Pathway Analysis: Annotating significant genes and identifying enriched biological pathways.
This toolkit is suitable for researchers and bioinformaticians working on gene expression studies and provides a streamlined workflow for extracting meaningful insights from large gene expression datasets.