From PCA to PCA-Plus: Advancing Principal Component Analysis for More Robust Data Interpretation
PCA (Principle Component Analysis) is a commonly used technique in biomedical research to identify similarities and differences between groups of samples. Though conventional PCA is a great tool, it still has some limitations in visualizing and quantifying batch effects; therefore, to overcome these limitations, researchers from the Department of Bioinformatics and Computational Biology, The University…