Rasvariation

Rasvariation is a statistical concept used in computational biology and genomics to quantify heterogeneity in Ras-related signaling across a population of samples. It measures how variable a Ras-related metric is among samples, providing a single scalar value that reflects dispersion relative to central tendency.

Calculation and methodology: It is often defined as the coefficient of variation of a Ras metric X across samples: Rasvariation equals the standard deviation of X divided by the mean of X. X can be gene expression level for a Ras family member, a computed activity score from a pathway model, or a phosphorylation level of a Ras effector. In some contexts, adjustments are made to account for measurement noise, sample size, or batch effects; alternative formulations may use robust statistics such as median absolute deviation or log-transformed data.

Origin and scope: The term Rasvariation emerged in discussions of tumor heterogeneity and pathway regulation, where Ras pathway activity varies across cells within a tumor or across tissues. It is used to compare heterogeneity between conditions (e.g., healthy versus diseased) or between genes within the Ras family.

Applications: Researchers use Rasvariation to identify samples or conditions with high heterogeneity, to assess the stability of therapeutic targets in Ras signaling, and to inform modeling of signaling dynamics. It can aid in stratifying patient samples for targeted therapies and in evaluating the consistency of signaling responses across experiments.

Limitations: Rasvariation is sensitive to outliers, sample size, and data normalization. It provides a summary measure and does not reveal specific patterns of which samples drive variability. Care is needed in interpretation and in selecting the appropriate metric X.