GMine WEB
GMine logo



Biomarker Discovery

Identify features predictive of an outcome of interest (e.g. responders/non-responders, disease/healthy, high risk/low risk). The discriminatory power of individual features can be assessed by area under the ROC curve (AUC), odds ratio, delta (difference in means in units of standard deviation), and fold change.

Set test to "LogisticRegression" to adjust p-values, AUC and OR for covariates (all covariates defined in meta annotation file).

Biomarker discovery can only be applied to data sets with exactly two groups.