Adjusting confounders in ranking biomarkers: a model-based ROC approach.

ABSTRACT: High-throughput studies have been extensively conducted in the research of complex human diseases. As a representative example, consider gene-expression studies where thousands of genes are profiled at the same time. An important objective of such studies is to rank the diagnostic accuracy of biomarkers (e.g. gene expressions) for predicting outcome variables while properly adjusting for confounding effects from low-dimensional clinical risk factors and environmental exposures. Existing approaches are often fully based on parametric or semi-parametric models and target evaluating estimation significance as opposed to diagnostic accuracy. Receiver operating characteristic (ROC) approaches can be employed to tackle this problem. However, existing ROC ranking methods focus on biomarkers only

SUBMITTER: Yu T 

PROVIDER: S-EPMC3431720 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature