Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.

ABSTRACT: Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used a

SUBMITTER: Yasrebi H 

PROVIDER: S-EPMC5863785 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature