correlation
Definition
Correlation is a statistical measure quantifying the strength and direction of association between two variables, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation). In biological research, correlation identifies co-occurring patterns in molecular data, such as gene expression levels, protein abundances, or metabolite concentrations. While correlation reveals relationships, it does not establish causation—a critical distinction in chain of causality frameworks. Correlated variables may share a causal relationship, be influenced by a common upstream factor, or associate by chance. Understanding correlation is foundational for hypothesis generation, biomarker discovery, and identifying potential regulatory relationships before applying causal inference methods.
Visualize correlation in Nodes Bio
Researchers can visualize correlation networks in Nodes Bio by representing molecules as nodes with edge weights indicating correlation strength. Color-coded edges can distinguish positive from negative correlations, while filtering thresholds reveal the strongest associations. This visualization helps identify co-expression modules, potential regulatory hubs, and candidate pathways for deeper causal analysis using perturbation data or directed acyclic graphs.
Visualization Ideas:
- Gene co-expression networks with correlation-weighted edges
- Metabolite correlation matrices showing pathway relationships
- Protein-protein interaction networks overlaid with expression correlation data
Example Use Case
A cancer researcher analyzes RNA-seq data from 500 tumor samples to identify genes correlated with patient survival outcomes. By constructing a correlation network, they discover a cluster of 15 highly correlated genes in the immune checkpoint pathway. While these genes show strong positive correlation with each other and negative correlation with tumor progression markers, the researcher recognizes this as hypothesis-generating evidence requiring functional validation experiments to establish causal mechanisms underlying therapeutic resistance.