confidence interval
Definition
A confidence interval is a statistical range that estimates the uncertainty around a measured value or effect size, typically expressed as a percentage (e.g., 95% CI). It indicates the range within which the true population parameter is likely to fall, based on sample data. In biological research, confidence intervals provide crucial context for interpreting experimental results, helping researchers distinguish between statistically significant findings and random variation. Unlike p-values alone, confidence intervals convey both the magnitude and precision of an effect, making them essential for assessing the reliability of biomarker associations, drug efficacy measurements, and gene expression differences. Wider intervals suggest greater uncertainty, while narrower intervals indicate more precise estimates.
Visualize confidence interval in Nodes Bio
In Nodes Bio, confidence intervals can be visualized as edge weights or node attributes in biological networks. Researchers can filter protein-protein interactions or gene regulatory relationships based on confidence thresholds, displaying only high-confidence connections. Edge thickness or color gradients can represent confidence levels, allowing users to quickly identify robust versus uncertain relationships in pathway analyses and prioritize experimental validation targets.
Visualization Ideas:
- Edge thickness proportional to confidence level in protein-protein interaction networks
- Color-coded nodes representing confidence intervals of gene expression fold-changes
- Network filtering to display only relationships exceeding confidence thresholds
Example Use Case
A pharmaceutical team investigating potential drug targets for Alzheimer's disease performs RNA-seq analysis comparing patient and control brain tissue. They identify 500 differentially expressed genes, each with fold-change estimates and 95% confidence intervals. Genes with narrow confidence intervals around large fold-changes represent high-confidence targets. By mapping these genes onto protein interaction networks in Nodes Bio and filtering by confidence interval width, researchers prioritize 15 hub proteins with robust expression changes for downstream validation studies.