Identification of Robust Pathway Markers for Cancer through Rank-Based Pathway Activity Inference.

ABSTRACT: One important problem in translational genomics is the identification of reliable and reproducible markers that can be used to discriminate between different classes of a complex disease, such as cancer. The typical small sample setting makes the prediction of such markers very challenging, and various approaches have been proposed to address this problem. For example, it has been shown that pathway markers, which aggregate the gene activities in the same pathway, tend to be more robust than gene markers. Furthermore, the use of gene expression ranking has been demonstrated to be robust to batch effects and that it can lead to more interpretable results. In this paper, we propose an enhanced pathway activity inference method that uses gene ranking to predict the pathway activity in a proba

SUBMITTER: Khunlertgit N 

PROVIDER: S-EPMC3600350 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature