Creating correlation matrix on genetic dataset

Create a correlation matrix using real-world data to analyze 11 genes linked to breast cancer tumor development. This workflow helps you observe expression rate variations between normal and cancerous breast tissue using a dataset of 572 entries. Steps include uploading files, previewing datasets, performing descriptive statistics, running normality tests, calculating Spearman’s rank correlation, visualizing correlation matrices, conducting the Mann-Whitney U test, and visualizing statistical significance via boxplots. This process aids in understanding gene expression differences and their potential implications in breast cancer research.