Recent advances in biomedical research have made massive amount of transcriptomic data available in public repositories from different sources. Due to the heterogeneity present in the individual experiments, identifying reproducible biomarkers for a given disease from multiple independent studies has become a major challenge. The widely used meta-analysis approaches, such as Fishers method, Stouffers method, minP and maxP, have at least two major limitations: i) they are sensitive to outliers, and ii) they perform only one statistical test for each individual study, and hence do not fully utilize the potential sample size to gain statistical power.