What Are the Challenges in Analyzing Gene Expression Data?
Analyzing gene expression data comes with several challenges. The data is often high-dimensional, meaning there are many more variables (genes) than samples. This requires sophisticated statistical and computational techniques to avoid overfitting and to identify meaningful patterns. Additionally, there is intrinsic biological variability and noise that can complicate analysis. Batch effects, where non-biological factors influence the data, also need to be corrected.
