The Power of Non-parametric Spearman Correlation in Multiomics Analysis plus AI Expansion
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Multiomics analysis, crucial in big data biology, benefits from Spearman correlation. This non-parametric method handles non-normal data and non-linear relationships, unlike traditional correlation. It focuses on ranked data, making it robust to outliers and capturing monotonic relationships. Spearman correlation aids in constructing robust correlation networks, revealing cross-talk between biological pathways and identifying biomarkers. Its versatility makes it applicable across diverse biological studies, enhancing precision in complex system analysis. It is essential for uncovering hidden biological relationships, driving advancements in precision medicine.